In [7]:
import sys
sys.path.insert(0,'../src/')

from data.make_dataset import *
from visualization.visualize import *
from models.models import *

%load_ext autoreload
%autoreload 1
The autoreload extension is already loaded. To reload it, use:
  %reload_ext autoreload
In [8]:
import torch
import numpy

if torch.cuda.is_available():
    prop = torch.cuda.get_device_properties(0)
    print(f"Using {prop.name} with {np.round(prop.total_memory/1e9, 2)}GB of RAM")
else:
    print("Using CPU")
Using GeForce GTX 1060 with Max-Q Design with 6.37GB of RAM

Load Data

In [9]:
channel_size = 3
image_size = 64
batch_size = 128
workers = 10
In [10]:
%%time
data_loader = make_dataloader("../data/raw/planctons_original", image_size, batch_size, workers)
CPU times: user 6.1 ms, sys: 3.91 ms, total: 10 ms
Wall time: 9.46 ms

Visualize Data

In [ ]:
print_samples(data_loader)

Load Models

In [14]:
latent_size = 100
feature_map_size = 64
In [15]:
beta = 0.5
lr = 0.0002
num_epochs = 2
In [16]:
g = DCGAN_Generator(latent_size, feature_map_size, channel_size)
d = DCGAN_Discriminator(feature_map_size, channel_size)

gan = GAN(d, g, lr, beta)

Train Model

In [17]:
%%time
gan.train(data_loader, 400)
Starting Training Loop...
[0/400][0/29]	Loss_D: 1.7484	Loss_G: 5.6300	D(x): 0.5497	D(G(z)): 0.5747 / 0.0057
[1/400][0/29]	Loss_D: 0.0386	Loss_G: 12.8821	D(x): 0.9650	D(G(z)): 0.0000 / 0.0000
Traceback (most recent call last):
  File "/home/gustavo/anaconda3/envs/ganenv/lib/python3.8/multiprocessing/queues.py", line 245, in _feed
    send_bytes(obj)
  File "/home/gustavo/anaconda3/envs/ganenv/lib/python3.8/multiprocessing/connection.py", line 200, in send_bytes
    self._send_bytes(m[offset:offset + size])
  File "/home/gustavo/anaconda3/envs/ganenv/lib/python3.8/multiprocessing/connection.py", line 411, in _send_bytes
    self._send(header + buf)
  File "/home/gustavo/anaconda3/envs/ganenv/lib/python3.8/multiprocessing/connection.py", line 368, in _send
    n = write(self._handle, buf)
BrokenPipeError: [Errno 32] Broken pipe
Traceback (most recent call last):
  File "/home/gustavo/anaconda3/envs/ganenv/lib/python3.8/multiprocessing/queues.py", line 245, in _feed
    send_bytes(obj)
  File "/home/gustavo/anaconda3/envs/ganenv/lib/python3.8/multiprocessing/connection.py", line 200, in send_bytes
    self._send_bytes(m[offset:offset + size])
  File "/home/gustavo/anaconda3/envs/ganenv/lib/python3.8/multiprocessing/connection.py", line 411, in _send_bytes
    self._send(header + buf)
  File "/home/gustavo/anaconda3/envs/ganenv/lib/python3.8/multiprocessing/connection.py", line 368, in _send
    n = write(self._handle, buf)
BrokenPipeError: [Errno 32] Broken pipe
---------------------------------------
KeyboardInterruptTraceback (most recent call last)
<timed eval> in <module>

~/gan_plankton/src/models/models.py in train(self, dataloader, num_epochs)
    162                 # Calculate gradients for D in backward pass
    163                 errD_real.backward()
--> 164                 D_x = output.mean().item()
    165 
    166                 ## Train with all-fake batch

KeyboardInterrupt: 
In [11]:
latent_size = 100
feature_map_size = 64

params_list = [{'beta': 0.5, 'lr': 0.002, 'num_epochs': 200},
               {'beta': 0.5, 'lr': 0.02, 'num_epochs': 200},
               {'beta': 0.5, 'lr': 0.0002, 'num_epochs': 200}]
In [13]:
%%time
i = 0
for params in params_list:
    i += 1
    print(f'\n------------------------\nAttempt {i}')
    
    g = DCGAN_Generator(latent_size, feature_map_size, channel_size)
    d = DCGAN_Discriminator(feature_map_size, channel_size)

    gan = GAN(d, g, params['lr'], params['beta'])
    gan.train(data_loader, params['num_epochs']) 
    
    plot_loss(gan.G_losses, gan.D_losses, img_path=f'../reports/model_analysis/loss_{i}.png')
    generator_progress(gan.img_list, gif_path=f'../reports/model_analysis/progress_{i}.gif')
    compare_fake_real(data_loader, gan.device, gan.img_list, img_path=f'../reports/model_analysis/comparison_{i}.png')
------------------------
Attempt 1
Starting Training Loop...
[0/200][0/29]	Loss_D: 2.2835	Loss_G: 32.6083	D(x): 0.3886	D(G(z)): 0.6013 / 0.0000
[1/200][0/29]	Loss_D: 1.1055	Loss_G: 2.7054	D(x): 0.5974	D(G(z)): 0.1396 / 0.1766
[2/200][0/29]	Loss_D: 1.9411	Loss_G: 1.3567	D(x): 0.5982	D(G(z)): 0.6294 / 0.3382
[3/200][0/29]	Loss_D: 1.0989	Loss_G: 1.7607	D(x): 0.6011	D(G(z)): 0.3605 / 0.2048
[4/200][0/29]	Loss_D: 1.1689	Loss_G: 1.3681	D(x): 0.6235	D(G(z)): 0.4219 / 0.3289
[5/200][0/29]	Loss_D: 1.6864	Loss_G: 2.1163	D(x): 0.7363	D(G(z)): 0.5133 / 0.1300
[6/200][0/29]	Loss_D: 1.1963	Loss_G: 1.8553	D(x): 0.6917	D(G(z)): 0.3842 / 0.2953
[7/200][0/29]	Loss_D: 0.9443	Loss_G: 2.2620	D(x): 0.8552	D(G(z)): 0.4518 / 0.1799
[8/200][0/29]	Loss_D: 0.8884	Loss_G: 4.3234	D(x): 0.8335	D(G(z)): 0.2097 / 0.0274
[9/200][0/29]	Loss_D: 1.8353	Loss_G: 1.2328	D(x): 0.6178	D(G(z)): 0.4301 / 0.3527
[10/200][0/29]	Loss_D: 1.4158	Loss_G: 2.9740	D(x): 0.7460	D(G(z)): 0.5850 / 0.1190
[11/200][0/29]	Loss_D: 0.8684	Loss_G: 1.1933	D(x): 0.7271	D(G(z)): 0.3852 / 0.3558
[12/200][0/29]	Loss_D: 1.6408	Loss_G: 5.7225	D(x): 0.7294	D(G(z)): 0.6215 / 0.0103
[13/200][0/29]	Loss_D: 0.9872	Loss_G: 2.1780	D(x): 0.6806	D(G(z)): 0.3905 / 0.2347
[14/200][0/29]	Loss_D: 1.7614	Loss_G: 3.0328	D(x): 0.6397	D(G(z)): 0.4790 / 0.0911
[15/200][0/29]	Loss_D: 1.7219	Loss_G: 1.8334	D(x): 0.7582	D(G(z)): 0.4968 / 0.2134
[16/200][0/29]	Loss_D: 0.6224	Loss_G: 2.4654	D(x): 0.7703	D(G(z)): 0.2799 / 0.1656
[17/200][0/29]	Loss_D: 1.3724	Loss_G: 1.3972	D(x): 0.4445	D(G(z)): 0.1803 / 0.3516
[18/200][0/29]	Loss_D: 1.5965	Loss_G: 1.6112	D(x): 0.5088	D(G(z)): 0.3901 / 0.2563
[19/200][0/29]	Loss_D: 1.2428	Loss_G: 4.2019	D(x): 0.8719	D(G(z)): 0.5107 / 0.0413
[20/200][0/29]	Loss_D: 1.3304	Loss_G: 0.4507	D(x): 0.3961	D(G(z)): 0.1865 / 0.6553
[21/200][0/29]	Loss_D: 1.3969	Loss_G: 1.6007	D(x): 0.7412	D(G(z)): 0.5214 / 0.2519
[22/200][0/29]	Loss_D: 1.5810	Loss_G: 2.1161	D(x): 0.9196	D(G(z)): 0.7304 / 0.1702
[23/200][0/29]	Loss_D: 0.9821	Loss_G: 2.7262	D(x): 0.8028	D(G(z)): 0.4680 / 0.0948
[24/200][0/29]	Loss_D: 0.7951	Loss_G: 2.7105	D(x): 0.7880	D(G(z)): 0.3744 / 0.1437
[25/200][0/29]	Loss_D: 1.1901	Loss_G: 1.7959	D(x): 0.5550	D(G(z)): 0.2464 / 0.2036
[26/200][0/29]	Loss_D: 0.7951	Loss_G: 4.0733	D(x): 0.6964	D(G(z)): 0.1901 / 0.0220
[27/200][0/29]	Loss_D: 1.8314	Loss_G: 3.5780	D(x): 0.3648	D(G(z)): 0.2412 / 0.0641
[28/200][0/29]	Loss_D: 1.8467	Loss_G: 3.0254	D(x): 0.6742	D(G(z)): 0.6759 / 0.0939
[29/200][0/29]	Loss_D: 1.0094	Loss_G: 1.6438	D(x): 0.5764	D(G(z)): 0.2658 / 0.2394
[30/200][0/29]	Loss_D: 0.9084	Loss_G: 1.4151	D(x): 0.5898	D(G(z)): 0.1890 / 0.3280
[31/200][0/29]	Loss_D: 1.3075	Loss_G: 3.6923	D(x): 0.6858	D(G(z)): 0.5092 / 0.0628
[32/200][0/29]	Loss_D: 0.9595	Loss_G: 1.2973	D(x): 0.5223	D(G(z)): 0.1547 / 0.3389
[33/200][0/29]	Loss_D: 1.0841	Loss_G: 1.9989	D(x): 0.5727	D(G(z)): 0.2577 / 0.1757
[34/200][0/29]	Loss_D: 1.1908	Loss_G: 3.0735	D(x): 0.9212	D(G(z)): 0.6022 / 0.0773
[35/200][0/29]	Loss_D: 1.2716	Loss_G: 3.0411	D(x): 0.9360	D(G(z)): 0.6407 / 0.0649
[36/200][0/29]	Loss_D: 1.1703	Loss_G: 1.4861	D(x): 0.4674	D(G(z)): 0.1953 / 0.3013
[37/200][0/29]	Loss_D: 0.8977	Loss_G: 2.8588	D(x): 0.8424	D(G(z)): 0.4206 / 0.1277
[38/200][0/29]	Loss_D: 0.7855	Loss_G: 2.6494	D(x): 0.6602	D(G(z)): 0.2604 / 0.1107
[39/200][0/29]	Loss_D: 0.7063	Loss_G: 2.7175	D(x): 0.7222	D(G(z)): 0.2469 / 0.1246
[40/200][0/29]	Loss_D: 1.2529	Loss_G: 0.6867	D(x): 0.5403	D(G(z)): 0.3915 / 0.5640
[41/200][0/29]	Loss_D: 0.9757	Loss_G: 2.0904	D(x): 0.7189	D(G(z)): 0.4133 / 0.1540
[42/200][0/29]	Loss_D: 1.6594	Loss_G: 4.2134	D(x): 0.9122	D(G(z)): 0.6735 / 0.0367
[43/200][0/29]	Loss_D: 1.0452	Loss_G: 2.6355	D(x): 0.6350	D(G(z)): 0.3749 / 0.1029
[44/200][0/29]	Loss_D: 0.7158	Loss_G: 1.8297	D(x): 0.7521	D(G(z)): 0.3159 / 0.1899
[45/200][0/29]	Loss_D: 0.6936	Loss_G: 2.3368	D(x): 0.7646	D(G(z)): 0.2920 / 0.1282
[46/200][0/29]	Loss_D: 0.8221	Loss_G: 1.7120	D(x): 0.6291	D(G(z)): 0.2094 / 0.2271
[47/200][0/29]	Loss_D: 0.6562	Loss_G: 3.3522	D(x): 0.7885	D(G(z)): 0.2657 / 0.0579
[48/200][0/29]	Loss_D: 0.9377	Loss_G: 2.4340	D(x): 0.7656	D(G(z)): 0.4246 / 0.1383
[49/200][0/29]	Loss_D: 0.7840	Loss_G: 2.2770	D(x): 0.7443	D(G(z)): 0.3057 / 0.1393
[50/200][0/29]	Loss_D: 0.9120	Loss_G: 1.2409	D(x): 0.5988	D(G(z)): 0.2436 / 0.3208
[51/200][0/29]	Loss_D: 0.7616	Loss_G: 2.2756	D(x): 0.6827	D(G(z)): 0.2226 / 0.1388
[52/200][0/29]	Loss_D: 0.9279	Loss_G: 1.3058	D(x): 0.5633	D(G(z)): 0.1874 / 0.3449
[53/200][0/29]	Loss_D: 0.7933	Loss_G: 2.6349	D(x): 0.8672	D(G(z)): 0.4267 / 0.0976
[54/200][0/29]	Loss_D: 1.4134	Loss_G: 1.8863	D(x): 0.7797	D(G(z)): 0.5985 / 0.2047
[55/200][0/29]	Loss_D: 1.1985	Loss_G: 1.1663	D(x): 0.5198	D(G(z)): 0.2889 / 0.3882
[56/200][0/29]	Loss_D: 0.8862	Loss_G: 1.8935	D(x): 0.6618	D(G(z)): 0.2749 / 0.2112
[57/200][0/29]	Loss_D: 0.7507	Loss_G: 2.4137	D(x): 0.7243	D(G(z)): 0.2708 / 0.1185
[58/200][0/29]	Loss_D: 0.9619	Loss_G: 2.9185	D(x): 0.6359	D(G(z)): 0.3225 / 0.0890
[59/200][0/29]	Loss_D: 0.8766	Loss_G: 3.9035	D(x): 0.8979	D(G(z)): 0.4391 / 0.0355
[60/200][0/29]	Loss_D: 0.5004	Loss_G: 2.6891	D(x): 0.7843	D(G(z)): 0.1800 / 0.1057
[61/200][0/29]	Loss_D: 1.0449	Loss_G: 2.5086	D(x): 0.7916	D(G(z)): 0.4732 / 0.1202
[62/200][0/29]	Loss_D: 0.7351	Loss_G: 2.3036	D(x): 0.7390	D(G(z)): 0.2913 / 0.1487
[63/200][0/29]	Loss_D: 0.8934	Loss_G: 2.3340	D(x): 0.5453	D(G(z)): 0.1322 / 0.1951
[64/200][0/29]	Loss_D: 1.0677	Loss_G: 3.0364	D(x): 0.6362	D(G(z)): 0.3603 / 0.0959
[65/200][0/29]	Loss_D: 1.4400	Loss_G: 5.7303	D(x): 0.8967	D(G(z)): 0.6834 / 0.0081
[66/200][0/29]	Loss_D: 0.4959	Loss_G: 4.5003	D(x): 0.9060	D(G(z)): 0.2920 / 0.0214
[67/200][0/29]	Loss_D: 1.0404	Loss_G: 1.3085	D(x): 0.5111	D(G(z)): 0.1413 / 0.3247
[68/200][0/29]	Loss_D: 0.8586	Loss_G: 3.1504	D(x): 0.7240	D(G(z)): 0.3560 / 0.0795
[69/200][0/29]	Loss_D: 1.0339	Loss_G: 2.6222	D(x): 0.8395	D(G(z)): 0.4926 / 0.1245
[70/200][0/29]	Loss_D: 0.7848	Loss_G: 2.8962	D(x): 0.5703	D(G(z)): 0.0509 / 0.0936
[71/200][0/29]	Loss_D: 0.6850	Loss_G: 3.7088	D(x): 0.8033	D(G(z)): 0.3128 / 0.0457
[72/200][0/29]	Loss_D: 0.6767	Loss_G: 2.7210	D(x): 0.8484	D(G(z)): 0.3236 / 0.1003
[73/200][0/29]	Loss_D: 0.5061	Loss_G: 3.2974	D(x): 0.7967	D(G(z)): 0.1960 / 0.0610
[74/200][0/29]	Loss_D: 0.7153	Loss_G: 3.4282	D(x): 0.8913	D(G(z)): 0.3672 / 0.0582
[75/200][0/29]	Loss_D: 1.0084	Loss_G: 4.0326	D(x): 0.9229	D(G(z)): 0.4856 / 0.0306
[76/200][0/29]	Loss_D: 1.4514	Loss_G: 1.2623	D(x): 0.3371	D(G(z)): 0.0848 / 0.3455
[77/200][0/29]	Loss_D: 0.9571	Loss_G: 1.2713	D(x): 0.5316	D(G(z)): 0.1444 / 0.3819
[78/200][0/29]	Loss_D: 1.1059	Loss_G: 2.7910	D(x): 0.8257	D(G(z)): 0.4941 / 0.0976
[79/200][0/29]	Loss_D: 1.0345	Loss_G: 2.7013	D(x): 0.8334	D(G(z)): 0.5057 / 0.0976
[80/200][0/29]	Loss_D: 1.0648	Loss_G: 1.9277	D(x): 0.4893	D(G(z)): 0.0787 / 0.2185
[81/200][0/29]	Loss_D: 0.7226	Loss_G: 2.7720	D(x): 0.8200	D(G(z)): 0.3361 / 0.0931
[82/200][0/29]	Loss_D: 0.8831	Loss_G: 4.1298	D(x): 0.8515	D(G(z)): 0.4504 / 0.0250
[83/200][0/29]	Loss_D: 0.6630	Loss_G: 3.5263	D(x): 0.7766	D(G(z)): 0.2497 / 0.0673
[84/200][0/29]	Loss_D: 1.0846	Loss_G: 2.5440	D(x): 0.6159	D(G(z)): 0.3510 / 0.1343
[85/200][0/29]	Loss_D: 0.6645	Loss_G: 2.6756	D(x): 0.8603	D(G(z)): 0.3412 / 0.1082
[86/200][0/29]	Loss_D: 1.3081	Loss_G: 2.7597	D(x): 0.7611	D(G(z)): 0.5619 / 0.1031
[87/200][0/29]	Loss_D: 1.1930	Loss_G: 3.3565	D(x): 0.8764	D(G(z)): 0.5612 / 0.0869
[88/200][0/29]	Loss_D: 0.6865	Loss_G: 2.5928	D(x): 0.7278	D(G(z)): 0.2437 / 0.1127
[89/200][0/29]	Loss_D: 1.0425	Loss_G: 3.5137	D(x): 0.7278	D(G(z)): 0.4248 / 0.1043
[90/200][0/29]	Loss_D: 0.7165	Loss_G: 2.2767	D(x): 0.6898	D(G(z)): 0.2388 / 0.1409
[91/200][0/29]	Loss_D: 1.3840	Loss_G: 1.7983	D(x): 0.4362	D(G(z)): 0.2398 / 0.2566
[92/200][0/29]	Loss_D: 0.6511	Loss_G: 3.8459	D(x): 0.9361	D(G(z)): 0.3975 / 0.0375
[93/200][0/29]	Loss_D: 0.6403	Loss_G: 2.5490	D(x): 0.7834	D(G(z)): 0.2705 / 0.1246
[94/200][0/29]	Loss_D: 0.9344	Loss_G: 2.3113	D(x): 0.4854	D(G(z)): 0.0689 / 0.1601
[95/200][0/29]	Loss_D: 0.6840	Loss_G: 3.6685	D(x): 0.8232	D(G(z)): 0.3227 / 0.0550
[96/200][0/29]	Loss_D: 1.6309	Loss_G: 3.2237	D(x): 0.8470	D(G(z)): 0.7041 / 0.0556
[97/200][0/29]	Loss_D: 1.3938	Loss_G: 1.7663	D(x): 0.4442	D(G(z)): 0.3226 / 0.2370
[98/200][0/29]	Loss_D: 1.4092	Loss_G: 1.8797	D(x): 0.3754	D(G(z)): 0.1760 / 0.2553
[99/200][0/29]	Loss_D: 0.7321	Loss_G: 2.9709	D(x): 0.7543	D(G(z)): 0.2730 / 0.0850
[100/200][0/29]	Loss_D: 0.9199	Loss_G: 3.6601	D(x): 0.7924	D(G(z)): 0.4143 / 0.0669
[101/200][0/29]	Loss_D: 1.3423	Loss_G: 4.4336	D(x): 0.9455	D(G(z)): 0.6418 / 0.0289
[102/200][0/29]	Loss_D: 0.6447	Loss_G: 2.9822	D(x): 0.7354	D(G(z)): 0.2080 / 0.1002
[103/200][0/29]	Loss_D: 1.2139	Loss_G: 1.2188	D(x): 0.4532	D(G(z)): 0.1438 / 0.3747
[104/200][0/29]	Loss_D: 0.8500	Loss_G: 2.2361	D(x): 0.6069	D(G(z)): 0.1712 / 0.1581
[105/200][0/29]	Loss_D: 0.6991	Loss_G: 2.5403	D(x): 0.6482	D(G(z)): 0.1298 / 0.1300
[106/200][0/29]	Loss_D: 1.5116	Loss_G: 1.6269	D(x): 0.3810	D(G(z)): 0.0756 / 0.2979
[107/200][0/29]	Loss_D: 0.7589	Loss_G: 3.2101	D(x): 0.7651	D(G(z)): 0.3178 / 0.0706
[108/200][0/29]	Loss_D: 0.4453	Loss_G: 3.5837	D(x): 0.8974	D(G(z)): 0.2484 / 0.0645
[109/200][0/29]	Loss_D: 0.4369	Loss_G: 3.3941	D(x): 0.8592	D(G(z)): 0.2041 / 0.0630
[110/200][0/29]	Loss_D: 0.7835	Loss_G: 2.9566	D(x): 0.6184	D(G(z)): 0.0999 / 0.1160
[111/200][0/29]	Loss_D: 0.4426	Loss_G: 4.0989	D(x): 0.8629	D(G(z)): 0.1848 / 0.0544
[112/200][0/29]	Loss_D: 0.7267	Loss_G: 4.7461	D(x): 0.8487	D(G(z)): 0.3532 / 0.0249
[113/200][0/29]	Loss_D: 0.5442	Loss_G: 3.9678	D(x): 0.8849	D(G(z)): 0.2849 / 0.0418
[114/200][0/29]	Loss_D: 0.6656	Loss_G: 3.8949	D(x): 0.6899	D(G(z)): 0.0723 / 0.0489
[115/200][0/29]	Loss_D: 0.5659	Loss_G: 3.6755	D(x): 0.8755	D(G(z)): 0.2892 / 0.0629
[116/200][0/29]	Loss_D: 0.8313	Loss_G: 5.1413	D(x): 0.8806	D(G(z)): 0.4035 / 0.0294
[117/200][0/29]	Loss_D: 0.7564	Loss_G: 5.0260	D(x): 0.9516	D(G(z)): 0.4335 / 0.0145
[118/200][0/29]	Loss_D: 0.6581	Loss_G: 3.2246	D(x): 0.6838	D(G(z)): 0.1664 / 0.0824
[119/200][0/29]	Loss_D: 1.0017	Loss_G: 2.2499	D(x): 0.5614	D(G(z)): 0.1789 / 0.2237
[120/200][0/29]	Loss_D: 0.3008	Loss_G: 3.7065	D(x): 0.8900	D(G(z)): 0.1340 / 0.0497
[121/200][0/29]	Loss_D: 0.6021	Loss_G: 3.5369	D(x): 0.7660	D(G(z)): 0.2107 / 0.0557
[122/200][0/29]	Loss_D: 0.6421	Loss_G: 6.3897	D(x): 0.9749	D(G(z)): 0.3953 / 0.0043
[123/200][0/29]	Loss_D: 0.5960	Loss_G: 3.4962	D(x): 0.7834	D(G(z)): 0.2240 / 0.0728
[124/200][0/29]	Loss_D: 0.7310	Loss_G: 3.7728	D(x): 0.7508	D(G(z)): 0.2735 / 0.0522
[125/200][0/29]	Loss_D: 0.6630	Loss_G: 5.9239	D(x): 0.9363	D(G(z)): 0.3697 / 0.0098
[126/200][0/29]	Loss_D: 0.5144	Loss_G: 3.5854	D(x): 0.7760	D(G(z)): 0.1505 / 0.0838
[127/200][0/29]	Loss_D: 0.3239	Loss_G: 3.3105	D(x): 0.8988	D(G(z)): 0.1636 / 0.0636
[128/200][0/29]	Loss_D: 1.3965	Loss_G: 7.7227	D(x): 0.9558	D(G(z)): 0.5548 / 0.0031
[129/200][0/29]	Loss_D: 0.7096	Loss_G: 5.0027	D(x): 0.8784	D(G(z)): 0.3355 / 0.0219
[130/200][0/29]	Loss_D: 0.4417	Loss_G: 2.8963	D(x): 0.7734	D(G(z)): 0.1177 / 0.1092
[131/200][0/29]	Loss_D: 0.4894	Loss_G: 5.2318	D(x): 0.9567	D(G(z)): 0.2912 / 0.0141
[132/200][0/29]	Loss_D: 0.3637	Loss_G: 3.5786	D(x): 0.8455	D(G(z)): 0.1354 / 0.0743
[133/200][0/29]	Loss_D: 0.8824	Loss_G: 3.1853	D(x): 0.5647	D(G(z)): 0.0360 / 0.1539
[134/200][0/29]	Loss_D: 0.2684	Loss_G: 4.7922	D(x): 0.9368	D(G(z)): 0.1561 / 0.0215
[135/200][0/29]	Loss_D: 0.5843	Loss_G: 2.6569	D(x): 0.6995	D(G(z)): 0.0877 / 0.1396
[136/200][0/29]	Loss_D: 0.5624	Loss_G: 6.5969	D(x): 0.9102	D(G(z)): 0.3120 / 0.0066
[137/200][0/29]	Loss_D: 0.4171	Loss_G: 4.2252	D(x): 0.8153	D(G(z)): 0.1401 / 0.0439
[138/200][0/29]	Loss_D: 0.5241	Loss_G: 4.7796	D(x): 0.9119	D(G(z)): 0.2764 / 0.0191
[139/200][0/29]	Loss_D: 0.3959	Loss_G: 5.8250	D(x): 0.9599	D(G(z)): 0.2508 / 0.0083
[140/200][0/29]	Loss_D: 0.6832	Loss_G: 3.6222	D(x): 0.6162	D(G(z)): 0.0516 / 0.1126
[141/200][0/29]	Loss_D: 0.4718	Loss_G: 4.3679	D(x): 0.8262	D(G(z)): 0.1721 / 0.0355
[142/200][0/29]	Loss_D: 0.8003	Loss_G: 3.1882	D(x): 0.5807	D(G(z)): 0.0446 / 0.1294
[143/200][0/29]	Loss_D: 0.2672	Loss_G: 5.9478	D(x): 0.9543	D(G(z)): 0.1483 / 0.0081
[144/200][0/29]	Loss_D: 0.3440	Loss_G: 6.7679	D(x): 0.9360	D(G(z)): 0.1978 / 0.0076
[145/200][0/29]	Loss_D: 0.5623	Loss_G: 5.3605	D(x): 0.9274	D(G(z)): 0.2840 / 0.0283
[146/200][0/29]	Loss_D: 0.4908	Loss_G: 5.7591	D(x): 0.8781	D(G(z)): 0.2232 / 0.0289
[147/200][0/29]	Loss_D: 0.5562	Loss_G: 3.9890	D(x): 0.7267	D(G(z)): 0.0561 / 0.0785
[148/200][0/29]	Loss_D: 0.4357	Loss_G: 5.6167	D(x): 0.9425	D(G(z)): 0.2550 / 0.0142
[149/200][0/29]	Loss_D: 0.4790	Loss_G: 4.8127	D(x): 0.7428	D(G(z)): 0.0569 / 0.0542
[150/200][0/29]	Loss_D: 0.3507	Loss_G: 4.8229	D(x): 0.8887	D(G(z)): 0.1499 / 0.0295
[151/200][0/29]	Loss_D: 0.3991	Loss_G: 8.0777	D(x): 0.9837	D(G(z)): 0.2293 / 0.0015
[152/200][0/29]	Loss_D: 0.3773	Loss_G: 3.5874	D(x): 0.7974	D(G(z)): 0.0787 / 0.0947
[153/200][0/29]	Loss_D: 0.7683	Loss_G: 5.4596	D(x): 0.9371	D(G(z)): 0.3716 / 0.0130
[154/200][0/29]	Loss_D: 0.3042	Loss_G: 5.7152	D(x): 0.9465	D(G(z)): 0.1651 / 0.0183
[155/200][0/29]	Loss_D: 0.4589	Loss_G: 6.0056	D(x): 0.9725	D(G(z)): 0.2587 / 0.0116
[156/200][0/29]	Loss_D: 0.2999	Loss_G: 4.6272	D(x): 0.8969	D(G(z)): 0.1324 / 0.0345
[157/200][0/29]	Loss_D: 0.1402	Loss_G: 4.3471	D(x): 0.9450	D(G(z)): 0.0666 / 0.0382
[158/200][0/29]	Loss_D: 1.1770	Loss_G: 10.5333	D(x): 0.9764	D(G(z)): 0.5582 / 0.0013
[159/200][0/29]	Loss_D: 0.4860	Loss_G: 4.6450	D(x): 0.7963	D(G(z)): 0.1385 / 0.0402
[160/200][0/29]	Loss_D: 0.2349	Loss_G: 6.6266	D(x): 0.9716	D(G(z)): 0.1528 / 0.0043
[161/200][0/29]	Loss_D: 0.1961	Loss_G: 5.9084	D(x): 0.8510	D(G(z)): 0.0073 / 0.0087
[162/200][0/29]	Loss_D: 0.2908	Loss_G: 4.8945	D(x): 0.9449	D(G(z)): 0.1520 / 0.0248
[163/200][0/29]	Loss_D: 0.4272	Loss_G: 5.6258	D(x): 0.9583	D(G(z)): 0.2375 / 0.0124
[164/200][0/29]	Loss_D: 0.2180	Loss_G: 5.3437	D(x): 0.9436	D(G(z)): 0.1156 / 0.0181
[165/200][0/29]	Loss_D: 0.6480	Loss_G: 7.4951	D(x): 0.9556	D(G(z)): 0.3533 / 0.0031
[166/200][0/29]	Loss_D: 0.3351	Loss_G: 5.3655	D(x): 0.8045	D(G(z)): 0.0317 / 0.0271
[167/200][0/29]	Loss_D: 0.2607	Loss_G: 6.5938	D(x): 0.9579	D(G(z)): 0.1239 / 0.0076
[168/200][0/29]	Loss_D: 0.3751	Loss_G: 5.1330	D(x): 0.8624	D(G(z)): 0.1254 / 0.0257
[169/200][0/29]	Loss_D: 0.3456	Loss_G: 6.5348	D(x): 0.9572	D(G(z)): 0.1699 / 0.0082
[170/200][0/29]	Loss_D: 0.0851	Loss_G: 6.1280	D(x): 0.9677	D(G(z)): 0.0443 / 0.0083
[171/200][0/29]	Loss_D: 0.2036	Loss_G: 5.8067	D(x): 0.9516	D(G(z)): 0.0942 / 0.0100
[172/200][0/29]	Loss_D: 0.2516	Loss_G: 5.7609	D(x): 0.8945	D(G(z)): 0.0749 / 0.0180
[173/200][0/29]	Loss_D: 1.1331	Loss_G: 8.5417	D(x): 0.9745	D(G(z)): 0.4362 / 0.0210
[174/200][0/29]	Loss_D: 0.2578	Loss_G: 5.8318	D(x): 0.9186	D(G(z)): 0.1041 / 0.0228
[175/200][0/29]	Loss_D: 0.2192	Loss_G: 4.3903	D(x): 0.8752	D(G(z)): 0.0518 / 0.0800
[176/200][0/29]	Loss_D: 0.1451	Loss_G: 5.1527	D(x): 0.9419	D(G(z)): 0.0606 / 0.0205
[177/200][0/29]	Loss_D: 0.1349	Loss_G: 5.9880	D(x): 0.9668	D(G(z)): 0.0771 / 0.0138
[178/200][0/29]	Loss_D: 0.1169	Loss_G: 6.7450	D(x): 0.9545	D(G(z)): 0.0474 / 0.0061
[179/200][0/29]	Loss_D: 0.1777	Loss_G: 5.0037	D(x): 0.9259	D(G(z)): 0.0657 / 0.0225
[180/200][0/29]	Loss_D: 0.3729	Loss_G: 8.8704	D(x): 0.9756	D(G(z)): 0.1991 / 0.0025
[181/200][0/29]	Loss_D: 0.7234	Loss_G: 3.8527	D(x): 0.7000	D(G(z)): 0.0727 / 0.1494
[182/200][0/29]	Loss_D: 0.2349	Loss_G: 5.5558	D(x): 0.9555	D(G(z)): 0.1236 / 0.0196
[183/200][0/29]	Loss_D: 0.2982	Loss_G: 6.2308	D(x): 0.8985	D(G(z)): 0.1047 / 0.0139
[184/200][0/29]	Loss_D: 0.1981	Loss_G: 6.9236	D(x): 0.9598	D(G(z)): 0.0999 / 0.0069
[185/200][0/29]	Loss_D: 0.1359	Loss_G: 6.3599	D(x): 0.9477	D(G(z)): 0.0640 / 0.0071
[186/200][0/29]	Loss_D: 0.0985	Loss_G: 5.7110	D(x): 0.9538	D(G(z)): 0.0391 / 0.0116
[187/200][0/29]	Loss_D: 1.4528	Loss_G: 11.0654	D(x): 0.9699	D(G(z)): 0.5705 / 0.0002
[188/200][0/29]	Loss_D: 0.3667	Loss_G: 5.5523	D(x): 0.8457	D(G(z)): 0.0974 / 0.0274
[189/200][0/29]	Loss_D: 0.2580	Loss_G: 4.8627	D(x): 0.8392	D(G(z)): 0.0309 / 0.0784
[190/200][0/29]	Loss_D: 0.0608	Loss_G: 5.1869	D(x): 0.9773	D(G(z)): 0.0293 / 0.0322
[191/200][0/29]	Loss_D: 0.0680	Loss_G: 5.9197	D(x): 0.9823	D(G(z)): 0.0412 / 0.0091
[192/200][0/29]	Loss_D: 0.2669	Loss_G: 8.0872	D(x): 0.9357	D(G(z)): 0.1133 / 0.0086
[193/200][0/29]	Loss_D: 0.0725	Loss_G: 6.6767	D(x): 0.9595	D(G(z)): 0.0256 / 0.0093
[194/200][0/29]	Loss_D: 0.8029	Loss_G: 4.8991	D(x): 0.6601	D(G(z)): 0.0500 / 0.1268
[195/200][0/29]	Loss_D: 0.3127	Loss_G: 5.0263	D(x): 0.8920	D(G(z)): 0.1058 / 0.0412
[196/200][0/29]	Loss_D: 0.0779	Loss_G: 7.8588	D(x): 0.9510	D(G(z)): 0.0208 / 0.0032
[197/200][0/29]	Loss_D: 0.1735	Loss_G: 6.8080	D(x): 0.9699	D(G(z)): 0.1109 / 0.0043
[198/200][0/29]	Loss_D: 0.2196	Loss_G: 8.8235	D(x): 0.9769	D(G(z)): 0.1421 / 0.0029
[199/200][0/29]	Loss_D: 0.5030	Loss_G: 9.8965	D(x): 0.9959	D(G(z)): 0.2848 / 0.0007
------------------------
Attempt 2
Starting Training Loop...
[0/200][0/29]	Loss_D: 1.9751	Loss_G: 66.9294	D(x): 0.6796	D(G(z)): 0.7195 / 0.0000
[1/200][0/29]	Loss_D: 12.4003	Loss_G: 4.1059	D(x): 0.9989	D(G(z)): 0.9637 / 0.3935
[2/200][0/29]	Loss_D: 4.2711	Loss_G: 2.0941	D(x): 0.3736	D(G(z)): 0.3233 / 0.2882
[3/200][0/29]	Loss_D: 3.7410	Loss_G: 3.4606	D(x): 0.7599	D(G(z)): 0.1623 / 0.1589
[4/200][0/29]	Loss_D: 1.7545	Loss_G: 5.4449	D(x): 0.8846	D(G(z)): 0.4961 / 0.0543
[5/200][0/29]	Loss_D: 3.0204	Loss_G: 0.7881	D(x): 0.8065	D(G(z)): 0.7084 / 0.6231
[6/200][0/29]	Loss_D: 1.5088	Loss_G: 2.0297	D(x): 0.6164	D(G(z)): 0.5791 / 0.1723
[7/200][0/29]	Loss_D: 0.8893	Loss_G: 3.8600	D(x): 0.7649	D(G(z)): 0.3564 / 0.0800
[8/200][0/29]	Loss_D: 1.7827	Loss_G: 9.2070	D(x): 0.9904	D(G(z)): 0.6952 / 0.0003
[9/200][0/29]	Loss_D: 0.1977	Loss_G: 4.0662	D(x): 0.9214	D(G(z)): 0.0734 / 0.0342
[10/200][0/29]	Loss_D: 1.3023	Loss_G: 7.6643	D(x): 0.8539	D(G(z)): 0.3017 / 0.0263
[11/200][0/29]	Loss_D: 0.3778	Loss_G: 3.2351	D(x): 0.8637	D(G(z)): 0.1009 / 0.0759
[12/200][0/29]	Loss_D: 0.1858	Loss_G: 4.8647	D(x): 0.9720	D(G(z)): 0.0636 / 0.0109
[13/200][0/29]	Loss_D: 0.1443	Loss_G: 5.4427	D(x): 0.9553	D(G(z)): 0.0818 / 0.0252
[14/200][0/29]	Loss_D: 0.1471	Loss_G: 6.8168	D(x): 0.9749	D(G(z)): 0.0671 / 0.0025
[15/200][0/29]	Loss_D: 0.3722	Loss_G: 3.9049	D(x): 0.9173	D(G(z)): 0.1273 / 0.0334
[16/200][0/29]	Loss_D: 0.7778	Loss_G: 9.3606	D(x): 0.9711	D(G(z)): 0.3316 / 0.0002
[17/200][0/29]	Loss_D: 0.1253	Loss_G: 4.0437	D(x): 0.9615	D(G(z)): 0.0787 / 0.0288
[18/200][0/29]	Loss_D: 0.9352	Loss_G: 6.1071	D(x): 0.6736	D(G(z)): 0.3531 / 0.0047
[19/200][0/29]	Loss_D: 0.3447	Loss_G: 2.6794	D(x): 0.7774	D(G(z)): 0.0597 / 0.1193
[20/200][0/29]	Loss_D: 1.2714	Loss_G: 2.0375	D(x): 0.6321	D(G(z)): 0.5039 / 0.1716
[21/200][0/29]	Loss_D: 0.9496	Loss_G: 1.2845	D(x): 0.5206	D(G(z)): 0.2018 / 0.3061
[22/200][0/29]	Loss_D: 3.5147	Loss_G: 0.4028	D(x): 0.0712	D(G(z)): 0.0410 / 0.7370
[23/200][0/29]	Loss_D: 0.1195	Loss_G: 3.6513	D(x): 0.9715	D(G(z)): 0.0821 / 0.0342
[24/200][0/29]	Loss_D: 1.2757	Loss_G: 1.8618	D(x): 0.8450	D(G(z)): 0.6559 / 0.2242
[25/200][0/29]	Loss_D: 1.1837	Loss_G: 1.3958	D(x): 0.7344	D(G(z)): 0.4527 / 0.3437
[26/200][0/29]	Loss_D: 2.5104	Loss_G: 0.4725	D(x): 0.1210	D(G(z)): 0.0910 / 0.6974
[27/200][0/29]	Loss_D: 4.3261	Loss_G: 0.9872	D(x): 0.0246	D(G(z)): 0.0024 / 0.4412
[28/200][0/29]	Loss_D: 0.5520	Loss_G: 3.2382	D(x): 0.7241	D(G(z)): 0.1671 / 0.0549
[29/200][0/29]	Loss_D: 0.8382	Loss_G: 3.4740	D(x): 0.7140	D(G(z)): 0.3450 / 0.0509
[30/200][0/29]	Loss_D: 0.1134	Loss_G: 3.6497	D(x): 0.9227	D(G(z)): 0.0276 / 0.0316
[31/200][0/29]	Loss_D: 0.5286	Loss_G: 2.9533	D(x): 0.7133	D(G(z)): 0.1007 / 0.0802
[32/200][0/29]	Loss_D: 1.1673	Loss_G: 1.9769	D(x): 0.6430	D(G(z)): 0.4484 / 0.1745
[33/200][0/29]	Loss_D: 1.1257	Loss_G: 4.4701	D(x): 0.6837	D(G(z)): 0.4738 / 0.0175
[34/200][0/29]	Loss_D: 0.4865	Loss_G: 3.9086	D(x): 0.8557	D(G(z)): 0.2604 / 0.0313
[35/200][0/29]	Loss_D: 0.1825	Loss_G: 11.8989	D(x): 0.8450	D(G(z)): 0.0000 / 0.0000
[36/200][0/29]	Loss_D: 1.7943	Loss_G: 8.1102	D(x): 0.9864	D(G(z)): 0.7640 / 0.0014
[37/200][0/29]	Loss_D: 0.7102	Loss_G: 2.7275	D(x): 0.6597	D(G(z)): 0.1875 / 0.0993
[38/200][0/29]	Loss_D: 0.6252	Loss_G: 1.5846	D(x): 0.7234	D(G(z)): 0.2332 / 0.2338
[39/200][0/29]	Loss_D: 1.5515	Loss_G: 2.1904	D(x): 0.6970	D(G(z)): 0.6271 / 0.1457
[40/200][0/29]	Loss_D: 0.7121	Loss_G: 2.3850	D(x): 0.7725	D(G(z)): 0.3058 / 0.1146
[41/200][0/29]	Loss_D: 0.2174	Loss_G: 3.3182	D(x): 0.9421	D(G(z)): 0.1419 / 0.0518
[42/200][0/29]	Loss_D: 0.7926	Loss_G: 2.0873	D(x): 0.7978	D(G(z)): 0.3885 / 0.1617
[43/200][0/29]	Loss_D: 1.1600	Loss_G: 1.2720	D(x): 0.7434	D(G(z)): 0.5040 / 0.3112
[44/200][0/29]	Loss_D: 0.6400	Loss_G: 2.1894	D(x): 0.7682	D(G(z)): 0.2820 / 0.1347
[45/200][0/29]	Loss_D: 1.7690	Loss_G: 1.9007	D(x): 0.4585	D(G(z)): 0.5386 / 0.2088
[46/200][0/29]	Loss_D: 1.0505	Loss_G: 1.3561	D(x): 0.5862	D(G(z)): 0.3436 / 0.2977
[47/200][0/29]	Loss_D: 0.8909	Loss_G: 2.6219	D(x): 0.7931	D(G(z)): 0.4205 / 0.0988
[48/200][0/29]	Loss_D: 1.5150	Loss_G: 1.8983	D(x): 0.6782	D(G(z)): 0.6094 / 0.1914
[49/200][0/29]	Loss_D: 1.1042	Loss_G: 0.9211	D(x): 0.4363	D(G(z)): 0.1233 / 0.5288
[50/200][0/29]	Loss_D: 1.2323	Loss_G: 4.0912	D(x): 0.7409	D(G(z)): 0.5085 / 0.0281
[51/200][0/29]	Loss_D: 1.5655	Loss_G: 1.5757	D(x): 0.7451	D(G(z)): 0.6942 / 0.2220
[52/200][0/29]	Loss_D: 1.3916	Loss_G: 1.0321	D(x): 0.3676	D(G(z)): 0.2203 / 0.4006
[53/200][0/29]	Loss_D: 0.8159	Loss_G: 2.2653	D(x): 0.7938	D(G(z)): 0.4005 / 0.1328
[54/200][0/29]	Loss_D: 1.0106	Loss_G: 2.1008	D(x): 0.6384	D(G(z)): 0.3703 / 0.1509
[55/200][0/29]	Loss_D: 3.7504	Loss_G: 1.0445	D(x): 0.0548	D(G(z)): 0.0364 / 0.3810
[56/200][0/29]	Loss_D: 6.3292	Loss_G: 1.0883	D(x): 0.0219	D(G(z)): 0.0023 / 0.3679
[57/200][0/29]	Loss_D: 1.2598	Loss_G: 0.7870	D(x): 0.4665	D(G(z)): 0.2967 / 0.4933
[58/200][0/29]	Loss_D: 3.6375	Loss_G: 1.7850	D(x): 0.0464	D(G(z)): 0.0360 / 0.2104
[59/200][0/29]	Loss_D: 1.2446	Loss_G: 1.6762	D(x): 0.4290	D(G(z)): 0.2432 / 0.2213
[60/200][0/29]	Loss_D: 0.6053	Loss_G: 2.1331	D(x): 0.7200	D(G(z)): 0.2093 / 0.1578
[61/200][0/29]	Loss_D: 1.5043	Loss_G: 3.4930	D(x): 0.3065	D(G(z)): 0.0043 / 0.0510
[62/200][0/29]	Loss_D: 0.4903	Loss_G: 2.5064	D(x): 0.7846	D(G(z)): 0.1754 / 0.1084
[63/200][0/29]	Loss_D: 2.5199	Loss_G: 1.0204	D(x): 0.1366	D(G(z)): 0.0800 / 0.4149
[64/200][0/29]	Loss_D: 2.1323	Loss_G: 1.7136	D(x): 0.2006	D(G(z)): 0.0505 / 0.2061
[65/200][0/29]	Loss_D: 3.2178	Loss_G: 5.0639	D(x): 0.9618	D(G(z)): 0.9206 / 0.0099
[66/200][0/29]	Loss_D: 1.2994	Loss_G: 1.5619	D(x): 0.5545	D(G(z)): 0.4403 / 0.2557
[67/200][0/29]	Loss_D: 1.0362	Loss_G: 5.3062	D(x): 0.9437	D(G(z)): 0.5484 / 0.0076
[68/200][0/29]	Loss_D: 1.8644	Loss_G: 4.7128	D(x): 0.8728	D(G(z)): 0.7468 / 0.0226
[69/200][0/29]	Loss_D: 0.6863	Loss_G: 4.3588	D(x): 0.9104	D(G(z)): 0.4186 / 0.0186
[70/200][0/29]	Loss_D: 1.3299	Loss_G: 0.6582	D(x): 0.3401	D(G(z)): 0.1249 / 0.5643
[71/200][0/29]	Loss_D: 0.8472	Loss_G: 1.7364	D(x): 0.6978	D(G(z)): 0.3395 / 0.2120
[72/200][0/29]	Loss_D: 0.8239	Loss_G: 2.1738	D(x): 0.9199	D(G(z)): 0.4826 / 0.1318
[73/200][0/29]	Loss_D: 1.1450	Loss_G: 2.0642	D(x): 0.6945	D(G(z)): 0.4777 / 0.1828
[74/200][0/29]	Loss_D: 0.9250	Loss_G: 2.1558	D(x): 0.6223	D(G(z)): 0.3001 / 0.1646
[75/200][0/29]	Loss_D: 0.6380	Loss_G: 2.3583	D(x): 0.7780	D(G(z)): 0.2536 / 0.1437
[76/200][0/29]	Loss_D: 1.1466	Loss_G: 1.5917	D(x): 0.6028	D(G(z)): 0.4066 / 0.2480
[77/200][0/29]	Loss_D: 0.7577	Loss_G: 1.6612	D(x): 0.6816	D(G(z)): 0.2360 / 0.2292
[78/200][0/29]	Loss_D: 1.3601	Loss_G: 2.1586	D(x): 0.8163	D(G(z)): 0.6346 / 0.1342
[79/200][0/29]	Loss_D: 1.1372	Loss_G: 2.5334	D(x): 0.8929	D(G(z)): 0.5853 / 0.1269
[80/200][0/29]	Loss_D: 1.4100	Loss_G: 0.7339	D(x): 0.3450	D(G(z)): 0.1676 / 0.5182
[81/200][0/29]	Loss_D: 0.9886	Loss_G: 2.1326	D(x): 0.7128	D(G(z)): 0.4331 / 0.1480
[82/200][0/29]	Loss_D: 0.9781	Loss_G: 1.1715	D(x): 0.5617	D(G(z)): 0.2669 / 0.3595
[83/200][0/29]	Loss_D: 1.2283	Loss_G: 3.3048	D(x): 0.6553	D(G(z)): 0.4407 / 0.0866
[84/200][0/29]	Loss_D: 1.2110	Loss_G: 2.3655	D(x): 0.9310	D(G(z)): 0.6161 / 0.1154
[85/200][0/29]	Loss_D: 1.0434	Loss_G: 1.3979	D(x): 0.7324	D(G(z)): 0.4756 / 0.2798
[86/200][0/29]	Loss_D: 2.1377	Loss_G: 1.4938	D(x): 0.8877	D(G(z)): 0.8306 / 0.2431
[87/200][0/29]	Loss_D: 0.9628	Loss_G: 3.7818	D(x): 0.8510	D(G(z)): 0.4757 / 0.0372
[88/200][0/29]	Loss_D: 0.9212	Loss_G: 2.1103	D(x): 0.6238	D(G(z)): 0.2802 / 0.1530
[89/200][0/29]	Loss_D: 0.9740	Loss_G: 2.3410	D(x): 0.7150	D(G(z)): 0.4255 / 0.1313
[90/200][0/29]	Loss_D: 1.0540	Loss_G: 1.6536	D(x): 0.6025	D(G(z)): 0.3860 / 0.2537
[91/200][0/29]	Loss_D: 0.8323	Loss_G: 3.1127	D(x): 0.8360	D(G(z)): 0.4317 / 0.0577
[92/200][0/29]	Loss_D: 0.9024	Loss_G: 1.7149	D(x): 0.5336	D(G(z)): 0.1227 / 0.2325
[93/200][0/29]	Loss_D: 1.1715	Loss_G: 1.4415	D(x): 0.4747	D(G(z)): 0.2145 / 0.3197
[94/200][0/29]	Loss_D: 1.2983	Loss_G: 1.1546	D(x): 0.4676	D(G(z)): 0.3313 / 0.4036
[95/200][0/29]	Loss_D: 0.5449	Loss_G: 4.2465	D(x): 0.7712	D(G(z)): 0.1987 / 0.0216
[96/200][0/29]	Loss_D: 1.3461	Loss_G: 1.7545	D(x): 0.4359	D(G(z)): 0.2541 / 0.2134
[97/200][0/29]	Loss_D: 2.0263	Loss_G: 1.3461	D(x): 0.2284	D(G(z)): 0.0966 / 0.3087
[98/200][0/29]	Loss_D: 0.7035	Loss_G: 2.6059	D(x): 0.7613	D(G(z)): 0.2990 / 0.0995
[99/200][0/29]	Loss_D: 0.6885	Loss_G: 2.5773	D(x): 0.6041	D(G(z)): 0.0897 / 0.0980
[100/200][0/29]	Loss_D: 1.0293	Loss_G: 0.8833	D(x): 0.6819	D(G(z)): 0.4282 / 0.4626
[101/200][0/29]	Loss_D: 0.2618	Loss_G: 4.6638	D(x): 0.8991	D(G(z)): 0.1340 / 0.0161
[102/200][0/29]	Loss_D: 0.7861	Loss_G: 4.8881	D(x): 0.9885	D(G(z)): 0.4847 / 0.0179
[103/200][0/29]	Loss_D: 0.1283	Loss_G: 4.0953	D(x): 0.9895	D(G(z)): 0.1058 / 0.0282
[104/200][0/29]	Loss_D: 1.0306	Loss_G: 4.6046	D(x): 0.8479	D(G(z)): 0.5019 / 0.0331
[105/200][0/29]	Loss_D: 0.9800	Loss_G: 3.5188	D(x): 0.8921	D(G(z)): 0.5129 / 0.0495
[106/200][0/29]	Loss_D: 1.3450	Loss_G: 3.4180	D(x): 0.6076	D(G(z)): 0.4647 / 0.0499
[107/200][0/29]	Loss_D: 0.9966	Loss_G: 4.0362	D(x): 0.7838	D(G(z)): 0.4277 / 0.0408
[108/200][0/29]	Loss_D: 1.2124	Loss_G: 1.8489	D(x): 0.8421	D(G(z)): 0.5850 / 0.2121
[109/200][0/29]	Loss_D: 0.8413	Loss_G: 3.2374	D(x): 0.8661	D(G(z)): 0.4466 / 0.0576
[110/200][0/29]	Loss_D: 0.7904	Loss_G: 2.8670	D(x): 0.7016	D(G(z)): 0.2574 / 0.0874
[111/200][0/29]	Loss_D: 1.0701	Loss_G: 2.1187	D(x): 0.6490	D(G(z)): 0.3206 / 0.1639
[112/200][0/29]	Loss_D: 1.2260	Loss_G: 2.6678	D(x): 0.6022	D(G(z)): 0.4170 / 0.1119
[113/200][0/29]	Loss_D: 1.1024	Loss_G: 1.4701	D(x): 0.4625	D(G(z)): 0.1577 / 0.3462
[114/200][0/29]	Loss_D: 0.8550	Loss_G: 1.8601	D(x): 0.6268	D(G(z)): 0.2498 / 0.2020
[115/200][0/29]	Loss_D: 0.7888	Loss_G: 1.2031	D(x): 0.5789	D(G(z)): 0.1100 / 0.4392
[116/200][0/29]	Loss_D: 0.7083	Loss_G: 3.8584	D(x): 0.8921	D(G(z)): 0.4049 / 0.0474
[117/200][0/29]	Loss_D: 0.7887	Loss_G: 3.3678	D(x): 0.7331	D(G(z)): 0.3039 / 0.0561
[118/200][0/29]	Loss_D: 2.2271	Loss_G: 6.2371	D(x): 0.9385	D(G(z)): 0.7683 / 0.0031
[119/200][0/29]	Loss_D: 0.6425	Loss_G: 5.0002	D(x): 0.8451	D(G(z)): 0.3116 / 0.0155
[120/200][0/29]	Loss_D: 0.6774	Loss_G: 2.6313	D(x): 0.6092	D(G(z)): 0.0582 / 0.1258
[121/200][0/29]	Loss_D: 1.3281	Loss_G: 4.1112	D(x): 0.9362	D(G(z)): 0.6122 / 0.0329
[122/200][0/29]	Loss_D: 1.0105	Loss_G: 3.1506	D(x): 0.7359	D(G(z)): 0.4094 / 0.0795
[123/200][0/29]	Loss_D: 0.6934	Loss_G: 4.5640	D(x): 0.7838	D(G(z)): 0.2984 / 0.0249
[124/200][0/29]	Loss_D: 0.9052	Loss_G: 2.5698	D(x): 0.5742	D(G(z)): 0.1455 / 0.1761
[125/200][0/29]	Loss_D: 1.2705	Loss_G: 4.1997	D(x): 0.9035	D(G(z)): 0.5955 / 0.0317
[126/200][0/29]	Loss_D: 0.6749	Loss_G: 4.2474	D(x): 0.9088	D(G(z)): 0.3806 / 0.0230
[127/200][0/29]	Loss_D: 1.0536	Loss_G: 3.3855	D(x): 0.9487	D(G(z)): 0.5260 / 0.0997
[128/200][0/29]	Loss_D: 0.5631	Loss_G: 3.0384	D(x): 0.7617	D(G(z)): 0.1810 / 0.1079
[129/200][0/29]	Loss_D: 0.7303	Loss_G: 3.6942	D(x): 0.7838	D(G(z)): 0.2924 / 0.0491
[130/200][0/29]	Loss_D: 0.5387	Loss_G: 3.7396	D(x): 0.8623	D(G(z)): 0.2519 / 0.0400
[131/200][0/29]	Loss_D: 0.7680	Loss_G: 2.8684	D(x): 0.6691	D(G(z)): 0.1948 / 0.1184
[132/200][0/29]	Loss_D: 0.3215	Loss_G: 3.9116	D(x): 0.8101	D(G(z)): 0.0297 / 0.0411
[133/200][0/29]	Loss_D: 1.4394	Loss_G: 7.0205	D(x): 0.9618	D(G(z)): 0.6531 / 0.0021
[134/200][0/29]	Loss_D: 0.8761	Loss_G: 4.0286	D(x): 0.9604	D(G(z)): 0.4676 / 0.0467
[135/200][0/29]	Loss_D: 0.4350	Loss_G: 3.1027	D(x): 0.7932	D(G(z)): 0.1429 / 0.0930
[136/200][0/29]	Loss_D: 0.3152	Loss_G: 3.1488	D(x): 0.8289	D(G(z)): 0.0871 / 0.0724
[137/200][0/29]	Loss_D: 1.1232	Loss_G: 6.6052	D(x): 0.9348	D(G(z)): 0.5291 / 0.0046
[138/200][0/29]	Loss_D: 0.7551	Loss_G: 2.7692	D(x): 0.6429	D(G(z)): 0.0419 / 0.1720
[139/200][0/29]	Loss_D: 1.5166	Loss_G: 6.8525	D(x): 0.9483	D(G(z)): 0.6858 / 0.0032
[140/200][0/29]	Loss_D: 0.6012	Loss_G: 3.7446	D(x): 0.8079	D(G(z)): 0.2437 / 0.0646
[141/200][0/29]	Loss_D: 0.3333	Loss_G: 7.9246	D(x): 0.9852	D(G(z)): 0.2118 / 0.0017
[142/200][0/29]	Loss_D: 0.7650	Loss_G: 2.5486	D(x): 0.8452	D(G(z)): 0.3621 / 0.1274
[143/200][0/29]	Loss_D: 0.4099	Loss_G: 4.5433	D(x): 0.8585	D(G(z)): 0.1821 / 0.0199
[144/200][0/29]	Loss_D: 0.4872	Loss_G: 4.2445	D(x): 0.8085	D(G(z)): 0.1744 / 0.0333
[145/200][0/29]	Loss_D: 0.3651	Loss_G: 4.6325	D(x): 0.8702	D(G(z)): 0.1400 / 0.0205
[146/200][0/29]	Loss_D: 2.8417	Loss_G: 6.7404	D(x): 0.1457	D(G(z)): 0.0007 / 0.0425
[147/200][0/29]	Loss_D: 2.5167	Loss_G: 7.1884	D(x): 0.9839	D(G(z)): 0.8545 / 0.0055
[148/200][0/29]	Loss_D: 0.8964	Loss_G: 1.2590	D(x): 0.6174	D(G(z)): 0.1768 / 0.3568
[149/200][0/29]	Loss_D: 0.6820	Loss_G: 3.9271	D(x): 0.6326	D(G(z)): 0.0668 / 0.0535
[150/200][0/29]	Loss_D: 1.8979	Loss_G: 9.1887	D(x): 0.9950	D(G(z)): 0.7415 / 0.0007
[151/200][0/29]	Loss_D: 0.9859	Loss_G: 6.0849	D(x): 0.9365	D(G(z)): 0.4622 / 0.0084
[152/200][0/29]	Loss_D: 0.5578	Loss_G: 6.1723	D(x): 0.9274	D(G(z)): 0.3115 / 0.0067
[153/200][0/29]	Loss_D: 0.2158	Loss_G: 5.3003	D(x): 0.9390	D(G(z)): 0.0860 / 0.0126
[154/200][0/29]	Loss_D: 0.4628	Loss_G: 7.5250	D(x): 0.9516	D(G(z)): 0.2503 / 0.0028
[155/200][0/29]	Loss_D: 0.9081	Loss_G: 5.3791	D(x): 0.5726	D(G(z)): 0.0137 / 0.0285
[156/200][0/29]	Loss_D: 0.3874	Loss_G: 3.8241	D(x): 0.8557	D(G(z)): 0.1571 / 0.0534
[157/200][0/29]	Loss_D: 0.6303	Loss_G: 2.5302	D(x): 0.6580	D(G(z)): 0.0685 / 0.1787
[158/200][0/29]	Loss_D: 1.0661	Loss_G: 7.3054	D(x): 0.9680	D(G(z)): 0.5191 / 0.0027
[159/200][0/29]	Loss_D: 0.6059	Loss_G: 12.8963	D(x): 0.9664	D(G(z)): 0.3512 / 0.0002
[160/200][0/29]	Loss_D: 0.2949	Loss_G: 4.7012	D(x): 0.8601	D(G(z)): 0.1010 / 0.0246
[161/200][0/29]	Loss_D: 0.3380	Loss_G: 3.9627	D(x): 0.8722	D(G(z)): 0.1446 / 0.0416
[162/200][0/29]	Loss_D: 0.2733	Loss_G: 5.5427	D(x): 0.9569	D(G(z)): 0.1604 / 0.0162
[163/200][0/29]	Loss_D: 0.4982	Loss_G: 6.3878	D(x): 0.9402	D(G(z)): 0.2982 / 0.0080
[164/200][0/29]	Loss_D: 0.5999	Loss_G: 3.0015	D(x): 0.6625	D(G(z)): 0.0254 / 0.1031
[165/200][0/29]	Loss_D: 0.2393	Loss_G: 6.0414	D(x): 0.8570	D(G(z)): 0.0405 / 0.0070
[166/200][0/29]	Loss_D: 0.6344	Loss_G: 6.8651	D(x): 0.7999	D(G(z)): 0.2286 / 0.0071
[167/200][0/29]	Loss_D: 1.0181	Loss_G: 2.0890	D(x): 0.7256	D(G(z)): 0.2500 / 0.2027
[168/200][0/29]	Loss_D: 0.7652	Loss_G: 3.1896	D(x): 0.6888	D(G(z)): 0.1087 / 0.1253
[169/200][0/29]	Loss_D: 1.8008	Loss_G: 0.3881	D(x): 0.3184	D(G(z)): 0.0279 / 0.7581
[170/200][0/29]	Loss_D: 1.4647	Loss_G: 3.1712	D(x): 0.3770	D(G(z)): 0.0099 / 0.1645
[171/200][0/29]	Loss_D: 0.3866	Loss_G: 3.6163	D(x): 0.9417	D(G(z)): 0.2061 / 0.0582
[172/200][0/29]	Loss_D: 1.5385	Loss_G: 10.1382	D(x): 0.9877	D(G(z)): 0.6164 / 0.0004
[173/200][0/29]	Loss_D: 0.5035	Loss_G: 3.2289	D(x): 0.7159	D(G(z)): 0.0766 / 0.1514
[174/200][0/29]	Loss_D: 0.8912	Loss_G: 10.3584	D(x): 0.9543	D(G(z)): 0.4667 / 0.0003
[175/200][0/29]	Loss_D: 0.3573	Loss_G: 4.0062	D(x): 0.8039	D(G(z)): 0.0508 / 0.0433
[176/200][0/29]	Loss_D: 0.3440	Loss_G: 4.7981	D(x): 0.8207	D(G(z)): 0.0871 / 0.0307
[177/200][0/29]	Loss_D: 0.8048	Loss_G: 5.9978	D(x): 0.5690	D(G(z)): 0.0029 / 0.0119
[178/200][0/29]	Loss_D: 0.9462	Loss_G: 6.1787	D(x): 0.9267	D(G(z)): 0.3510 / 0.0086
[179/200][0/29]	Loss_D: 0.0366	Loss_G: 6.2566	D(x): 0.9825	D(G(z)): 0.0164 / 0.0135
[180/200][0/29]	Loss_D: 1.1179	Loss_G: 3.6820	D(x): 0.5724	D(G(z)): 0.0660 / 0.0983
[181/200][0/29]	Loss_D: 0.9000	Loss_G: 7.0798	D(x): 0.9540	D(G(z)): 0.4480 / 0.0065
[182/200][0/29]	Loss_D: 0.1423	Loss_G: 6.8391	D(x): 0.9680	D(G(z)): 0.0810 / 0.0103
[183/200][0/29]	Loss_D: 1.7081	Loss_G: 7.4436	D(x): 0.9891	D(G(z)): 0.6731 / 0.0071
[184/200][0/29]	Loss_D: 2.3040	Loss_G: 2.5461	D(x): 0.2316	D(G(z)): 0.0007 / 0.3582
[185/200][0/29]	Loss_D: 1.1815	Loss_G: 12.3839	D(x): 0.9920	D(G(z)): 0.4778 / 0.0000
[186/200][0/29]	Loss_D: 0.6197	Loss_G: 9.4907	D(x): 0.9822	D(G(z)): 0.3353 / 0.0004
[187/200][0/29]	Loss_D: 0.0118	Loss_G: 10.8918	D(x): 0.9891	D(G(z)): 0.0003 / 0.0004
[188/200][0/29]	Loss_D: 0.2507	Loss_G: 5.9260	D(x): 0.8640	D(G(z)): 0.0325 / 0.0314
[189/200][0/29]	Loss_D: 1.6216	Loss_G: 7.9644	D(x): 0.3297	D(G(z)): 0.0005 / 0.0191
[190/200][0/29]	Loss_D: 0.1006	Loss_G: 6.3627	D(x): 0.9734	D(G(z)): 0.0547 / 0.0095
[191/200][0/29]	Loss_D: 0.5573	Loss_G: 3.4582	D(x): 0.7901	D(G(z)): 0.1121 / 0.0951
[192/200][0/29]	Loss_D: 0.5376	Loss_G: 5.6361	D(x): 0.7106	D(G(z)): 0.0109 / 0.0323
[193/200][0/29]	Loss_D: 0.2363	Loss_G: 5.9708	D(x): 0.8560	D(G(z)): 0.0288 / 0.0093
[194/200][0/29]	Loss_D: 0.6321	Loss_G: 11.2579	D(x): 0.9524	D(G(z)): 0.3169 / 0.0003
[195/200][0/29]	Loss_D: 0.4710	Loss_G: 11.1584	D(x): 0.9265	D(G(z)): 0.2132 / 0.0004
[196/200][0/29]	Loss_D: 0.2261	Loss_G: 6.5116	D(x): 0.9634	D(G(z)): 0.1357 / 0.0073
[197/200][0/29]	Loss_D: 1.1561	Loss_G: 2.5541	D(x): 0.5643	D(G(z)): 0.0846 / 0.3014
[198/200][0/29]	Loss_D: 0.0569	Loss_G: 7.4992	D(x): 0.9790	D(G(z)): 0.0301 / 0.0038
[199/200][0/29]	Loss_D: 0.2802	Loss_G: 8.3995	D(x): 0.9877	D(G(z)): 0.1732 / 0.0021
------------------------
Attempt 3
Starting Training Loop...
[0/200][0/29]	Loss_D: 1.6919	Loss_G: 3.5758	D(x): 0.3966	D(G(z)): 0.4336 / 0.0397
[1/200][0/29]	Loss_D: 0.0017	Loss_G: 24.3003	D(x): 0.9983	D(G(z)): 0.0000 / 0.0000
[2/200][0/29]	Loss_D: 0.2443	Loss_G: 24.2967	D(x): 0.8415	D(G(z)): 0.0000 / 0.0000
[3/200][0/29]	Loss_D: 0.3429	Loss_G: 9.2204	D(x): 0.7760	D(G(z)): 0.0074 / 0.0003
[4/200][0/29]	Loss_D: 0.2953	Loss_G: 2.4491	D(x): 0.8370	D(G(z)): 0.0988 / 0.1013
[5/200][0/29]	Loss_D: 0.7030	Loss_G: 1.7735	D(x): 0.6478	D(G(z)): 0.2077 / 0.1995
[6/200][0/29]	Loss_D: 0.7444	Loss_G: 5.0542	D(x): 0.9334	D(G(z)): 0.4540 / 0.0141
[7/200][0/29]	Loss_D: 0.4598	Loss_G: 5.6356	D(x): 0.7155	D(G(z)): 0.0238 / 0.0198
[8/200][0/29]	Loss_D: 0.2347	Loss_G: 6.0450	D(x): 0.9129	D(G(z)): 0.1203 / 0.0038
[9/200][0/29]	Loss_D: 3.3479	Loss_G: 1.8203	D(x): 0.1113	D(G(z)): 0.0013 / 0.2342
[10/200][0/29]	Loss_D: 0.1400	Loss_G: 3.6535	D(x): 0.9264	D(G(z)): 0.0585 / 0.0338
[11/200][0/29]	Loss_D: 0.3777	Loss_G: 5.4987	D(x): 0.8467	D(G(z)): 0.1636 / 0.0062
[12/200][0/29]	Loss_D: 0.9476	Loss_G: 7.7428	D(x): 0.4697	D(G(z)): 0.0024 / 0.0043
[13/200][0/29]	Loss_D: 0.5612	Loss_G: 2.2834	D(x): 0.6270	D(G(z)): 0.0278 / 0.2538
[14/200][0/29]	Loss_D: 0.1280	Loss_G: 3.6601	D(x): 0.9235	D(G(z)): 0.0452 / 0.0291
[15/200][0/29]	Loss_D: 0.1674	Loss_G: 4.4131	D(x): 0.9187	D(G(z)): 0.0748 / 0.0133
[16/200][0/29]	Loss_D: 0.0986	Loss_G: 5.4124	D(x): 0.9581	D(G(z)): 0.0465 / 0.0053
[17/200][0/29]	Loss_D: 0.3304	Loss_G: 4.6639	D(x): 0.9160	D(G(z)): 0.1794 / 0.0144
[18/200][0/29]	Loss_D: 1.0156	Loss_G: 0.6390	D(x): 0.4691	D(G(z)): 0.0979 / 0.5887
[19/200][0/29]	Loss_D: 0.7462	Loss_G: 2.3211	D(x): 0.7894	D(G(z)): 0.3626 / 0.1185
[20/200][0/29]	Loss_D: 2.8919	Loss_G: 3.3485	D(x): 0.9691	D(G(z)): 0.9260 / 0.0471
[21/200][0/29]	Loss_D: 0.8944	Loss_G: 1.9260	D(x): 0.6665	D(G(z)): 0.3295 / 0.1717
[22/200][0/29]	Loss_D: 0.7873	Loss_G: 1.1228	D(x): 0.6001	D(G(z)): 0.1533 / 0.3638
[23/200][0/29]	Loss_D: 0.6751	Loss_G: 3.1319	D(x): 0.8347	D(G(z)): 0.3608 / 0.0536
[24/200][0/29]	Loss_D: 0.9361	Loss_G: 1.6986	D(x): 0.5244	D(G(z)): 0.1418 / 0.2200
[25/200][0/29]	Loss_D: 0.3727	Loss_G: 2.6489	D(x): 0.8543	D(G(z)): 0.1760 / 0.0920
[26/200][0/29]	Loss_D: 0.6820	Loss_G: 2.4776	D(x): 0.7977	D(G(z)): 0.3297 / 0.0996
[27/200][0/29]	Loss_D: 0.9816	Loss_G: 1.5207	D(x): 0.4584	D(G(z)): 0.0384 / 0.2979
[28/200][0/29]	Loss_D: 0.3168	Loss_G: 3.4402	D(x): 0.8262	D(G(z)): 0.1044 / 0.0471
[29/200][0/29]	Loss_D: 0.2820	Loss_G: 3.7696	D(x): 0.8584	D(G(z)): 0.1029 / 0.0273
[30/200][0/29]	Loss_D: 2.7104	Loss_G: 6.7191	D(x): 0.9551	D(G(z)): 0.9012 / 0.0024
[31/200][0/29]	Loss_D: 0.3727	Loss_G: 3.5944	D(x): 0.8283	D(G(z)): 0.1528 / 0.0348
[32/200][0/29]	Loss_D: 0.7845	Loss_G: 3.0368	D(x): 0.7629	D(G(z)): 0.3433 / 0.0721
[33/200][0/29]	Loss_D: 0.4794	Loss_G: 3.2676	D(x): 0.8472	D(G(z)): 0.2510 / 0.0513
[34/200][0/29]	Loss_D: 0.5115	Loss_G: 3.4815	D(x): 0.8319	D(G(z)): 0.2493 / 0.0434
[35/200][0/29]	Loss_D: 0.4789	Loss_G: 3.4776	D(x): 0.8148	D(G(z)): 0.2040 / 0.0415
[36/200][0/29]	Loss_D: 0.3362	Loss_G: 3.5134	D(x): 0.8276	D(G(z)): 0.1155 / 0.0400
[37/200][0/29]	Loss_D: 1.2338	Loss_G: 4.9664	D(x): 0.9303	D(G(z)): 0.6087 / 0.0108
[38/200][0/29]	Loss_D: 0.5490	Loss_G: 1.6642	D(x): 0.7092	D(G(z)): 0.1286 / 0.2378
[39/200][0/29]	Loss_D: 0.3061	Loss_G: 3.2860	D(x): 0.8947	D(G(z)): 0.1568 / 0.0512
[40/200][0/29]	Loss_D: 0.5232	Loss_G: 4.3621	D(x): 0.8423	D(G(z)): 0.2596 / 0.0178
[41/200][0/29]	Loss_D: 2.1780	Loss_G: 0.5943	D(x): 0.1677	D(G(z)): 0.0318 / 0.5862
[42/200][0/29]	Loss_D: 0.4510	Loss_G: 3.3788	D(x): 0.9623	D(G(z)): 0.3234 / 0.0473
[43/200][0/29]	Loss_D: 0.4779	Loss_G: 2.9969	D(x): 0.9461	D(G(z)): 0.3210 / 0.0619
[44/200][0/29]	Loss_D: 0.9613	Loss_G: 1.3177	D(x): 0.4882	D(G(z)): 0.1171 / 0.3415
[45/200][0/29]	Loss_D: 0.8098	Loss_G: 1.6339	D(x): 0.5082	D(G(z)): 0.0420 / 0.2210
[46/200][0/29]	Loss_D: 0.3973	Loss_G: 4.5190	D(x): 0.8042	D(G(z)): 0.1314 / 0.0183
[47/200][0/29]	Loss_D: 0.4322	Loss_G: 3.4465	D(x): 0.8704	D(G(z)): 0.2364 / 0.0400
[48/200][0/29]	Loss_D: 1.0237	Loss_G: 5.3219	D(x): 0.9580	D(G(z)): 0.5771 / 0.0087
[49/200][0/29]	Loss_D: 0.4694	Loss_G: 3.5509	D(x): 0.8891	D(G(z)): 0.2828 / 0.0348
[50/200][0/29]	Loss_D: 0.6890	Loss_G: 4.0468	D(x): 0.8843	D(G(z)): 0.3947 / 0.0236
[51/200][0/29]	Loss_D: 0.7531	Loss_G: 2.9151	D(x): 0.7321	D(G(z)): 0.2770 / 0.0783
[52/200][0/29]	Loss_D: 0.2497	Loss_G: 4.9013	D(x): 0.9282	D(G(z)): 0.1486 / 0.0131
[53/200][0/29]	Loss_D: 1.4567	Loss_G: 4.0037	D(x): 0.8785	D(G(z)): 0.6835 / 0.0327
[54/200][0/29]	Loss_D: 0.4709	Loss_G: 4.9134	D(x): 0.6586	D(G(z)): 0.0151 / 0.0176
[55/200][0/29]	Loss_D: 0.4229	Loss_G: 4.0040	D(x): 0.8786	D(G(z)): 0.2308 / 0.0256
[56/200][0/29]	Loss_D: 0.9897	Loss_G: 0.8101	D(x): 0.4325	D(G(z)): 0.0432 / 0.5107
[57/200][0/29]	Loss_D: 0.8086	Loss_G: 4.6352	D(x): 0.9010	D(G(z)): 0.4842 / 0.0133
[58/200][0/29]	Loss_D: 0.5366	Loss_G: 2.7604	D(x): 0.8013	D(G(z)): 0.2442 / 0.0861
[59/200][0/29]	Loss_D: 0.6207	Loss_G: 2.9377	D(x): 0.6690	D(G(z)): 0.1430 / 0.0791
[60/200][0/29]	Loss_D: 0.4540	Loss_G: 3.5037	D(x): 0.9192	D(G(z)): 0.2740 / 0.0470
[61/200][0/29]	Loss_D: 0.9069	Loss_G: 1.8625	D(x): 0.4726	D(G(z)): 0.0455 / 0.1994
[62/200][0/29]	Loss_D: 0.8963	Loss_G: 0.8906	D(x): 0.4912	D(G(z)): 0.0951 / 0.4766
[63/200][0/29]	Loss_D: 0.8233	Loss_G: 0.8737	D(x): 0.5640	D(G(z)): 0.1504 / 0.4618
[64/200][0/29]	Loss_D: 0.6732	Loss_G: 3.7945	D(x): 0.9047	D(G(z)): 0.3970 / 0.0322
[65/200][0/29]	Loss_D: 0.3086	Loss_G: 3.3587	D(x): 0.8805	D(G(z)): 0.1550 / 0.0482
[66/200][0/29]	Loss_D: 0.6541	Loss_G: 4.0405	D(x): 0.9066	D(G(z)): 0.3895 / 0.0252
[67/200][0/29]	Loss_D: 0.8442	Loss_G: 4.1337	D(x): 0.4918	D(G(z)): 0.0108 / 0.0268
[68/200][0/29]	Loss_D: 0.4523	Loss_G: 2.3963	D(x): 0.7140	D(G(z)): 0.0765 / 0.1263
[69/200][0/29]	Loss_D: 0.9388	Loss_G: 4.5463	D(x): 0.9774	D(G(z)): 0.5620 / 0.0149
[70/200][0/29]	Loss_D: 0.4129	Loss_G: 3.2654	D(x): 0.8398	D(G(z)): 0.1917 / 0.0514
[71/200][0/29]	Loss_D: 0.5553	Loss_G: 2.2811	D(x): 0.6242	D(G(z)): 0.0231 / 0.1286
[72/200][0/29]	Loss_D: 0.9827	Loss_G: 2.1069	D(x): 0.4841	D(G(z)): 0.0262 / 0.1597
[73/200][0/29]	Loss_D: 0.6984	Loss_G: 4.0612	D(x): 0.9133	D(G(z)): 0.4055 / 0.0275
[74/200][0/29]	Loss_D: 0.5455	Loss_G: 2.6654	D(x): 0.8393	D(G(z)): 0.2746 / 0.0939
[75/200][0/29]	Loss_D: 0.3162	Loss_G: 4.0582	D(x): 0.8291	D(G(z)): 0.0953 / 0.0257
[76/200][0/29]	Loss_D: 0.7308	Loss_G: 2.3281	D(x): 0.5392	D(G(z)): 0.0256 / 0.1525
[77/200][0/29]	Loss_D: 0.7276	Loss_G: 1.6552	D(x): 0.6123	D(G(z)): 0.1228 / 0.2417
[78/200][0/29]	Loss_D: 0.3426	Loss_G: 3.7327	D(x): 0.8579	D(G(z)): 0.1586 / 0.0306
[79/200][0/29]	Loss_D: 0.3377	Loss_G: 3.1353	D(x): 0.8719	D(G(z)): 0.1482 / 0.0635
[80/200][0/29]	Loss_D: 1.0110	Loss_G: 6.0048	D(x): 0.9707	D(G(z)): 0.5483 / 0.0049
[81/200][0/29]	Loss_D: 0.5030	Loss_G: 4.4006	D(x): 0.9228	D(G(z)): 0.3140 / 0.0229
[82/200][0/29]	Loss_D: 0.8281	Loss_G: 5.7145	D(x): 0.9211	D(G(z)): 0.4862 / 0.0051
[83/200][0/29]	Loss_D: 0.3612	Loss_G: 2.8661	D(x): 0.8165	D(G(z)): 0.1268 / 0.0753
[84/200][0/29]	Loss_D: 0.3017	Loss_G: 3.8754	D(x): 0.8568	D(G(z)): 0.1192 / 0.0342
[85/200][0/29]	Loss_D: 0.5822	Loss_G: 3.2599	D(x): 0.7959	D(G(z)): 0.2639 / 0.0555
[86/200][0/29]	Loss_D: 0.3042	Loss_G: 2.7522	D(x): 0.8623	D(G(z)): 0.1320 / 0.0851
[87/200][0/29]	Loss_D: 0.3411	Loss_G: 3.5200	D(x): 0.8359	D(G(z)): 0.1256 / 0.0428
[88/200][0/29]	Loss_D: 0.2497	Loss_G: 3.1211	D(x): 0.9118	D(G(z)): 0.1358 / 0.0657
[89/200][0/29]	Loss_D: 0.4030	Loss_G: 3.1789	D(x): 0.8167	D(G(z)): 0.1557 / 0.0641
[90/200][0/29]	Loss_D: 0.6020	Loss_G: 5.3412	D(x): 0.9783	D(G(z)): 0.3850 / 0.0096
[91/200][0/29]	Loss_D: 0.3347	Loss_G: 3.7150	D(x): 0.8099	D(G(z)): 0.0988 / 0.0339
[92/200][0/29]	Loss_D: 0.5496	Loss_G: 4.1633	D(x): 0.6265	D(G(z)): 0.0128 / 0.0459
[93/200][0/29]	Loss_D: 0.3594	Loss_G: 3.6608	D(x): 0.9074	D(G(z)): 0.2083 / 0.0356
[94/200][0/29]	Loss_D: 1.6572	Loss_G: 5.9731	D(x): 0.9866	D(G(z)): 0.7088 / 0.0066
[95/200][0/29]	Loss_D: 1.6805	Loss_G: 5.7784	D(x): 0.9925	D(G(z)): 0.7583 / 0.0065
[96/200][0/29]	Loss_D: 0.1611	Loss_G: 2.8033	D(x): 0.9143	D(G(z)): 0.0637 / 0.0790
[97/200][0/29]	Loss_D: 0.5304	Loss_G: 4.3010	D(x): 0.8243	D(G(z)): 0.2553 / 0.0208
[98/200][0/29]	Loss_D: 0.4506	Loss_G: 5.7690	D(x): 0.9663	D(G(z)): 0.3121 / 0.0051
[99/200][0/29]	Loss_D: 0.2274	Loss_G: 3.7448	D(x): 0.8778	D(G(z)): 0.0795 / 0.0446
[100/200][0/29]	Loss_D: 0.2278	Loss_G: 2.2476	D(x): 0.8756	D(G(z)): 0.0773 / 0.1568
[101/200][0/29]	Loss_D: 1.0943	Loss_G: 6.9977	D(x): 0.9743	D(G(z)): 0.5940 / 0.0025
[102/200][0/29]	Loss_D: 0.1414	Loss_G: 4.6583	D(x): 0.9283	D(G(z)): 0.0590 / 0.0141
[103/200][0/29]	Loss_D: 0.6926	Loss_G: 6.1033	D(x): 0.9566	D(G(z)): 0.4306 / 0.0052
[104/200][0/29]	Loss_D: 0.5699	Loss_G: 5.6320	D(x): 0.9708	D(G(z)): 0.3745 / 0.0053
[105/200][0/29]	Loss_D: 0.8684	Loss_G: 2.0502	D(x): 0.5175	D(G(z)): 0.0075 / 0.1730
[106/200][0/29]	Loss_D: 0.6212	Loss_G: 6.1123	D(x): 0.9564	D(G(z)): 0.3929 / 0.0034
[107/200][0/29]	Loss_D: 0.1547	Loss_G: 3.1552	D(x): 0.9347	D(G(z)): 0.0785 / 0.0638
[108/200][0/29]	Loss_D: 0.2084	Loss_G: 3.0026	D(x): 0.9373	D(G(z)): 0.1165 / 0.0955
[109/200][0/29]	Loss_D: 0.6049	Loss_G: 4.5160	D(x): 0.9832	D(G(z)): 0.3706 / 0.0178
[110/200][0/29]	Loss_D: 0.3379	Loss_G: 3.1584	D(x): 0.8723	D(G(z)): 0.1659 / 0.0623
[111/200][0/29]	Loss_D: 0.4187	Loss_G: 5.1438	D(x): 0.9612	D(G(z)): 0.2859 / 0.0089
[112/200][0/29]	Loss_D: 0.7236	Loss_G: 6.8368	D(x): 0.9902	D(G(z)): 0.4512 / 0.0021
[113/200][0/29]	Loss_D: 0.1992	Loss_G: 3.9624	D(x): 0.9835	D(G(z)): 0.1477 / 0.0291
[114/200][0/29]	Loss_D: 0.5511	Loss_G: 5.0258	D(x): 0.9584	D(G(z)): 0.3571 / 0.0100
[115/200][0/29]	Loss_D: 0.3889	Loss_G: 4.6397	D(x): 0.9744	D(G(z)): 0.2746 / 0.0175
[116/200][0/29]	Loss_D: 0.5926	Loss_G: 5.3438	D(x): 0.9558	D(G(z)): 0.3687 / 0.0081
[117/200][0/29]	Loss_D: 0.3317	Loss_G: 3.9607	D(x): 0.9645	D(G(z)): 0.2254 / 0.0275
[118/200][0/29]	Loss_D: 0.4744	Loss_G: 5.3757	D(x): 0.9774	D(G(z)): 0.3062 / 0.0084
[119/200][0/29]	Loss_D: 0.1221	Loss_G: 3.8970	D(x): 0.9377	D(G(z)): 0.0527 / 0.0355
[120/200][0/29]	Loss_D: 2.8506	Loss_G: 7.3343	D(x): 0.9916	D(G(z)): 0.9023 / 0.0016
[121/200][0/29]	Loss_D: 0.2626	Loss_G: 2.8696	D(x): 0.8590	D(G(z)): 0.0932 / 0.0804
[122/200][0/29]	Loss_D: 0.6766	Loss_G: 1.4965	D(x): 0.5990	D(G(z)): 0.0781 / 0.2875
[123/200][0/29]	Loss_D: 0.4316	Loss_G: 2.3644	D(x): 0.6976	D(G(z)): 0.0302 / 0.1335
[124/200][0/29]	Loss_D: 0.3812	Loss_G: 4.6432	D(x): 0.9814	D(G(z)): 0.2869 / 0.0144
[125/200][0/29]	Loss_D: 0.3022	Loss_G: 3.3826	D(x): 0.8782	D(G(z)): 0.1429 / 0.0507
[126/200][0/29]	Loss_D: 0.5513	Loss_G: 2.5618	D(x): 0.6380	D(G(z)): 0.0230 / 0.1342
[127/200][0/29]	Loss_D: 0.3456	Loss_G: 4.1876	D(x): 0.9493	D(G(z)): 0.2343 / 0.0210
[128/200][0/29]	Loss_D: 0.1288	Loss_G: 4.4410	D(x): 0.9483	D(G(z)): 0.0675 / 0.0181
[129/200][0/29]	Loss_D: 0.6023	Loss_G: 6.5510	D(x): 0.9866	D(G(z)): 0.3979 / 0.0026
[130/200][0/29]	Loss_D: 0.6231	Loss_G: 3.3214	D(x): 0.9407	D(G(z)): 0.3692 / 0.0634
[131/200][0/29]	Loss_D: 0.3662	Loss_G: 2.5155	D(x): 0.7889	D(G(z)): 0.0932 / 0.1226
[132/200][0/29]	Loss_D: 0.5270	Loss_G: 2.1233	D(x): 0.6369	D(G(z)): 0.0113 / 0.1751
[133/200][0/29]	Loss_D: 0.2918	Loss_G: 4.0943	D(x): 0.9320	D(G(z)): 0.1853 / 0.0257
[134/200][0/29]	Loss_D: 0.4416	Loss_G: 4.5842	D(x): 0.9445	D(G(z)): 0.2918 / 0.0223
[135/200][0/29]	Loss_D: 0.1340	Loss_G: 3.7435	D(x): 0.9505	D(G(z)): 0.0751 / 0.0358
[136/200][0/29]	Loss_D: 1.8295	Loss_G: 7.4098	D(x): 0.9962	D(G(z)): 0.7206 / 0.0026
[137/200][0/29]	Loss_D: 0.3794	Loss_G: 2.9927	D(x): 0.7478	D(G(z)): 0.0555 / 0.0854
[138/200][0/29]	Loss_D: 0.1477	Loss_G: 4.8500	D(x): 0.9104	D(G(z)): 0.0451 / 0.0140
[139/200][0/29]	Loss_D: 0.1892	Loss_G: 3.2492	D(x): 0.9066	D(G(z)): 0.0811 / 0.0535
[140/200][0/29]	Loss_D: 0.1827	Loss_G: 3.0683	D(x): 0.9484	D(G(z)): 0.1137 / 0.0707
[141/200][0/29]	Loss_D: 0.2072	Loss_G: 3.5212	D(x): 0.9252	D(G(z)): 0.1116 / 0.0481
[142/200][0/29]	Loss_D: 0.2802	Loss_G: 5.6606	D(x): 0.7878	D(G(z)): 0.0080 / 0.0113
[143/200][0/29]	Loss_D: 0.2968	Loss_G: 3.9169	D(x): 0.8083	D(G(z)): 0.0512 / 0.0372
[144/200][0/29]	Loss_D: 0.2745	Loss_G: 4.0905	D(x): 0.8095	D(G(z)): 0.0415 / 0.0317
[145/200][0/29]	Loss_D: 0.1456	Loss_G: 3.6782	D(x): 0.9031	D(G(z)): 0.0379 / 0.0383
[146/200][0/29]	Loss_D: 3.2540	Loss_G: 9.6398	D(x): 0.9992	D(G(z)): 0.9206 / 0.0004
[147/200][0/29]	Loss_D: 0.6006	Loss_G: 5.7920	D(x): 0.9768	D(G(z)): 0.3687 / 0.0074
[148/200][0/29]	Loss_D: 0.3326	Loss_G: 4.2664	D(x): 0.9268	D(G(z)): 0.2026 / 0.0242
[149/200][0/29]	Loss_D: 0.1659	Loss_G: 3.8353	D(x): 0.9511	D(G(z)): 0.1036 / 0.0323
[150/200][0/29]	Loss_D: 0.1852	Loss_G: 3.0983	D(x): 0.8667	D(G(z)): 0.0343 / 0.0757
[151/200][0/29]	Loss_D: 0.4448	Loss_G: 4.8393	D(x): 0.9477	D(G(z)): 0.2830 / 0.0148
[152/200][0/29]	Loss_D: 0.3797	Loss_G: 5.9062	D(x): 0.9650	D(G(z)): 0.2520 / 0.0056
[153/200][0/29]	Loss_D: 0.2142	Loss_G: 3.1126	D(x): 0.8888	D(G(z)): 0.0817 / 0.0595
[154/200][0/29]	Loss_D: 0.1375	Loss_G: 4.4360	D(x): 0.9096	D(G(z)): 0.0331 / 0.0261
[155/200][0/29]	Loss_D: 0.2435	Loss_G: 3.3263	D(x): 0.8422	D(G(z)): 0.0486 / 0.0586
[156/200][0/29]	Loss_D: 0.1523	Loss_G: 3.9945	D(x): 0.8893	D(G(z)): 0.0238 / 0.0329
[157/200][0/29]	Loss_D: 0.7794	Loss_G: 6.0971	D(x): 0.9698	D(G(z)): 0.4353 / 0.0045
[158/200][0/29]	Loss_D: 0.3719	Loss_G: 4.7599	D(x): 0.9812	D(G(z)): 0.2548 / 0.0166
[159/200][0/29]	Loss_D: 2.0389	Loss_G: 10.1373	D(x): 0.9928	D(G(z)): 0.7327 / 0.0004
[160/200][0/29]	Loss_D: 0.3568	Loss_G: 4.0789	D(x): 0.8788	D(G(z)): 0.1754 / 0.0296
[161/200][0/29]	Loss_D: 0.2395	Loss_G: 3.2149	D(x): 0.8896	D(G(z)): 0.1003 / 0.0607
[162/200][0/29]	Loss_D: 0.3788	Loss_G: 3.9503	D(x): 0.9729	D(G(z)): 0.2715 / 0.0274
[163/200][0/29]	Loss_D: 0.1468	Loss_G: 3.7616	D(x): 0.9356	D(G(z)): 0.0727 / 0.0372
[164/200][0/29]	Loss_D: 0.1612	Loss_G: 3.9790	D(x): 0.9419	D(G(z)): 0.0905 / 0.0293
[165/200][0/29]	Loss_D: 0.7553	Loss_G: 7.7398	D(x): 0.9930	D(G(z)): 0.4488 / 0.0008
[166/200][0/29]	Loss_D: 0.1678	Loss_G: 3.7915	D(x): 0.9135	D(G(z)): 0.0685 / 0.0360
[167/200][0/29]	Loss_D: 0.0980	Loss_G: 4.2978	D(x): 0.9439	D(G(z)): 0.0372 / 0.0249
[168/200][0/29]	Loss_D: 0.0954	Loss_G: 4.6805	D(x): 0.9524	D(G(z)): 0.0423 / 0.0160
[169/200][0/29]	Loss_D: 0.1297	Loss_G: 3.5591	D(x): 0.9560	D(G(z)): 0.0758 / 0.0496
[170/200][0/29]	Loss_D: 1.1637	Loss_G: 1.9073	D(x): 0.5178	D(G(z)): 0.2003 / 0.3122
[171/200][0/29]	Loss_D: 0.5310	Loss_G: 4.3686	D(x): 0.9302	D(G(z)): 0.3291 / 0.0186
[172/200][0/29]	Loss_D: 0.2821	Loss_G: 2.9949	D(x): 0.8155	D(G(z)): 0.0593 / 0.0763
[173/200][0/29]	Loss_D: 0.2264	Loss_G: 3.8713	D(x): 0.8707	D(G(z)): 0.0723 / 0.0348
[174/200][0/29]	Loss_D: 0.2194	Loss_G: 3.0420	D(x): 0.9038	D(G(z)): 0.1003 / 0.0703
[175/200][0/29]	Loss_D: 0.2372	Loss_G: 3.0622	D(x): 0.8983	D(G(z)): 0.1081 / 0.0733
[176/200][0/29]	Loss_D: 0.2624	Loss_G: 4.0727	D(x): 0.9720	D(G(z)): 0.1907 / 0.0274
[177/200][0/29]	Loss_D: 0.2331	Loss_G: 3.7759	D(x): 0.8495	D(G(z)): 0.0409 / 0.0515
[178/200][0/29]	Loss_D: 0.3835	Loss_G: 2.6801	D(x): 0.7612	D(G(z)): 0.0775 / 0.1033
[179/200][0/29]	Loss_D: 0.1967	Loss_G: 3.7066	D(x): 0.9374	D(G(z)): 0.1127 / 0.0390
[180/200][0/29]	Loss_D: 0.5053	Loss_G: 5.3566	D(x): 0.9192	D(G(z)): 0.2887 / 0.0118
[181/200][0/29]	Loss_D: 0.2325	Loss_G: 3.8824	D(x): 0.9609	D(G(z)): 0.1570 / 0.0313
[182/200][0/29]	Loss_D: 0.6169	Loss_G: 3.0302	D(x): 0.6255	D(G(z)): 0.0151 / 0.1141
[183/200][0/29]	Loss_D: 0.4280	Loss_G: 6.1672	D(x): 0.9612	D(G(z)): 0.2778 / 0.0032
[184/200][0/29]	Loss_D: 0.3192	Loss_G: 4.3766	D(x): 0.8395	D(G(z)): 0.0986 / 0.0231
[185/200][0/29]	Loss_D: 0.1891	Loss_G: 3.5325	D(x): 0.9007	D(G(z)): 0.0707 / 0.0484
[186/200][0/29]	Loss_D: 0.1737	Loss_G: 3.9259	D(x): 0.9747	D(G(z)): 0.1269 / 0.0276
[187/200][0/29]	Loss_D: 1.9621	Loss_G: 9.3239	D(x): 0.9766	D(G(z)): 0.7380 / 0.0003
[188/200][0/29]	Loss_D: 0.1817	Loss_G: 4.1876	D(x): 0.9078	D(G(z)): 0.0734 / 0.0252
[189/200][0/29]	Loss_D: 0.2697	Loss_G: 3.2769	D(x): 0.8454	D(G(z)): 0.0819 / 0.0590
[190/200][0/29]	Loss_D: 0.2039	Loss_G: 3.2097	D(x): 0.9446	D(G(z)): 0.1240 / 0.0690
[191/200][0/29]	Loss_D: 0.1162	Loss_G: 3.4329	D(x): 0.9729	D(G(z)): 0.0807 / 0.0485
[192/200][0/29]	Loss_D: 0.2079	Loss_G: 3.9653	D(x): 0.8834	D(G(z)): 0.0720 / 0.0330
[193/200][0/29]	Loss_D: 0.1961	Loss_G: 3.5648	D(x): 0.9383	D(G(z)): 0.1159 / 0.0438
[194/200][0/29]	Loss_D: 0.3211	Loss_G: 3.1483	D(x): 0.8591	D(G(z)): 0.1144 / 0.0879
[195/200][0/29]	Loss_D: 0.2123	Loss_G: 4.5620	D(x): 0.9694	D(G(z)): 0.1527 / 0.0165
[196/200][0/29]	Loss_D: 0.1626	Loss_G: 4.9394	D(x): 0.9811	D(G(z)): 0.1244 / 0.0111
[197/200][0/29]	Loss_D: 0.1073	Loss_G: 3.9928	D(x): 0.9204	D(G(z)): 0.0203 / 0.0324
[198/200][0/29]	Loss_D: 0.1109	Loss_G: 4.3211	D(x): 0.9711	D(G(z)): 0.0737 / 0.0218
[199/200][0/29]	Loss_D: 0.3434	Loss_G: 5.3806	D(x): 0.9279	D(G(z)): 0.2140 / 0.0077
------------------------
Attempt 4
Starting Training Loop...
[0/400][0/29]	Loss_D: 1.3558	Loss_G: 29.2974	D(x): 0.4940	D(G(z)): 0.3844 / 0.0000
[1/400][0/29]	Loss_D: 27.6310	Loss_G: 0.0000	D(x): 1.0000	D(G(z)): 1.0000 / 1.0000
[2/400][0/29]	Loss_D: 27.6310	Loss_G: 0.0000	D(x): 1.0000	D(G(z)): 1.0000 / 1.0000
[3/400][0/29]	Loss_D: 27.6310	Loss_G: 0.0000	D(x): 1.0000	D(G(z)): 1.0000 / 1.0000
[4/400][0/29]	Loss_D: 27.6310	Loss_G: 0.0000	D(x): 1.0000	D(G(z)): 1.0000 / 1.0000
[5/400][0/29]	Loss_D: 27.6310	Loss_G: 0.0000	D(x): 1.0000	D(G(z)): 1.0000 / 1.0000
[6/400][0/29]	Loss_D: 27.6310	Loss_G: 0.0000	D(x): 1.0000	D(G(z)): 1.0000 / 1.0000
[7/400][0/29]	Loss_D: 27.6310	Loss_G: 0.0000	D(x): 1.0000	D(G(z)): 1.0000 / 1.0000
[8/400][0/29]	Loss_D: 27.6310	Loss_G: 0.0000	D(x): 1.0000	D(G(z)): 1.0000 / 1.0000
[9/400][0/29]	Loss_D: 27.6310	Loss_G: 0.0000	D(x): 1.0000	D(G(z)): 1.0000 / 1.0000
[10/400][0/29]	Loss_D: 27.6310	Loss_G: 0.0000	D(x): 1.0000	D(G(z)): 1.0000 / 1.0000
[11/400][0/29]	Loss_D: 27.6310	Loss_G: 0.0000	D(x): 1.0000	D(G(z)): 1.0000 / 1.0000
[12/400][0/29]	Loss_D: 27.6310	Loss_G: 0.0000	D(x): 1.0000	D(G(z)): 1.0000 / 1.0000
[13/400][0/29]	Loss_D: 27.6310	Loss_G: 0.0000	D(x): 1.0000	D(G(z)): 1.0000 / 1.0000
[14/400][0/29]	Loss_D: 27.6310	Loss_G: 0.0000	D(x): 1.0000	D(G(z)): 1.0000 / 1.0000
[15/400][0/29]	Loss_D: 27.6310	Loss_G: 0.0000	D(x): 1.0000	D(G(z)): 1.0000 / 1.0000
[16/400][0/29]	Loss_D: 27.6310	Loss_G: 0.0000	D(x): 1.0000	D(G(z)): 1.0000 / 1.0000
[17/400][0/29]	Loss_D: 27.6310	Loss_G: 0.0000	D(x): 1.0000	D(G(z)): 1.0000 / 1.0000
[18/400][0/29]	Loss_D: 27.6310	Loss_G: 0.0000	D(x): 1.0000	D(G(z)): 1.0000 / 1.0000
[19/400][0/29]	Loss_D: 27.6310	Loss_G: 0.0000	D(x): 1.0000	D(G(z)): 1.0000 / 1.0000
[20/400][0/29]	Loss_D: 27.6310	Loss_G: 0.0000	D(x): 1.0000	D(G(z)): 1.0000 / 1.0000
[21/400][0/29]	Loss_D: 27.6310	Loss_G: 0.0000	D(x): 1.0000	D(G(z)): 1.0000 / 1.0000
[22/400][0/29]	Loss_D: 27.6310	Loss_G: 0.0000	D(x): 1.0000	D(G(z)): 1.0000 / 1.0000
[23/400][0/29]	Loss_D: 27.6310	Loss_G: 0.0000	D(x): 1.0000	D(G(z)): 1.0000 / 1.0000
[24/400][0/29]	Loss_D: 27.6310	Loss_G: 0.0000	D(x): 1.0000	D(G(z)): 1.0000 / 1.0000
[25/400][0/29]	Loss_D: 27.6310	Loss_G: 0.0000	D(x): 1.0000	D(G(z)): 1.0000 / 1.0000
[26/400][0/29]	Loss_D: 27.6310	Loss_G: 0.0000	D(x): 1.0000	D(G(z)): 1.0000 / 1.0000
[27/400][0/29]	Loss_D: 27.6310	Loss_G: 0.0000	D(x): 1.0000	D(G(z)): 1.0000 / 1.0000
[28/400][0/29]	Loss_D: 27.6310	Loss_G: 0.0000	D(x): 1.0000	D(G(z)): 1.0000 / 1.0000
[29/400][0/29]	Loss_D: 27.6310	Loss_G: 0.0000	D(x): 1.0000	D(G(z)): 1.0000 / 1.0000
[30/400][0/29]	Loss_D: 27.6310	Loss_G: 0.0000	D(x): 1.0000	D(G(z)): 1.0000 / 1.0000
[31/400][0/29]	Loss_D: 27.6310	Loss_G: 0.0000	D(x): 1.0000	D(G(z)): 1.0000 / 1.0000
[32/400][0/29]	Loss_D: 27.6310	Loss_G: 0.0000	D(x): 1.0000	D(G(z)): 1.0000 / 1.0000
[33/400][0/29]	Loss_D: 27.6310	Loss_G: 0.0000	D(x): 1.0000	D(G(z)): 1.0000 / 1.0000
[34/400][0/29]	Loss_D: 27.6310	Loss_G: 0.0000	D(x): 1.0000	D(G(z)): 1.0000 / 1.0000
[35/400][0/29]	Loss_D: 27.6310	Loss_G: 0.0000	D(x): 1.0000	D(G(z)): 1.0000 / 1.0000
[36/400][0/29]	Loss_D: 27.6310	Loss_G: 0.0000	D(x): 1.0000	D(G(z)): 1.0000 / 1.0000
[37/400][0/29]	Loss_D: 27.6310	Loss_G: 0.0000	D(x): 1.0000	D(G(z)): 1.0000 / 1.0000
[38/400][0/29]	Loss_D: 27.6310	Loss_G: 0.0000	D(x): 1.0000	D(G(z)): 1.0000 / 1.0000
[39/400][0/29]	Loss_D: 27.6310	Loss_G: 0.0000	D(x): 1.0000	D(G(z)): 1.0000 / 1.0000
[40/400][0/29]	Loss_D: 27.6310	Loss_G: 0.0000	D(x): 1.0000	D(G(z)): 1.0000 / 1.0000
[41/400][0/29]	Loss_D: 27.6310	Loss_G: 0.0000	D(x): 1.0000	D(G(z)): 1.0000 / 1.0000
[42/400][0/29]	Loss_D: 27.6310	Loss_G: 0.0000	D(x): 1.0000	D(G(z)): 1.0000 / 1.0000
[43/400][0/29]	Loss_D: 27.6310	Loss_G: 0.0000	D(x): 1.0000	D(G(z)): 1.0000 / 1.0000
[44/400][0/29]	Loss_D: 27.6310	Loss_G: 0.0000	D(x): 1.0000	D(G(z)): 1.0000 / 1.0000
[45/400][0/29]	Loss_D: 27.6310	Loss_G: 0.0000	D(x): 1.0000	D(G(z)): 1.0000 / 1.0000
[46/400][0/29]	Loss_D: 27.6310	Loss_G: 0.0000	D(x): 1.0000	D(G(z)): 1.0000 / 1.0000
[47/400][0/29]	Loss_D: 27.6310	Loss_G: 0.0000	D(x): 1.0000	D(G(z)): 1.0000 / 1.0000
[48/400][0/29]	Loss_D: 27.6310	Loss_G: 0.0000	D(x): 1.0000	D(G(z)): 1.0000 / 1.0000
[49/400][0/29]	Loss_D: 27.6310	Loss_G: 0.0000	D(x): 1.0000	D(G(z)): 1.0000 / 1.0000
[50/400][0/29]	Loss_D: 27.6310	Loss_G: 0.0000	D(x): 1.0000	D(G(z)): 1.0000 / 1.0000
[51/400][0/29]	Loss_D: 27.6310	Loss_G: 0.0000	D(x): 1.0000	D(G(z)): 1.0000 / 1.0000
[52/400][0/29]	Loss_D: 27.6310	Loss_G: 0.0000	D(x): 1.0000	D(G(z)): 1.0000 / 1.0000
[53/400][0/29]	Loss_D: 27.6310	Loss_G: 0.0000	D(x): 1.0000	D(G(z)): 1.0000 / 1.0000
[54/400][0/29]	Loss_D: 27.6310	Loss_G: 0.0000	D(x): 1.0000	D(G(z)): 1.0000 / 1.0000
[55/400][0/29]	Loss_D: 27.6310	Loss_G: 0.0000	D(x): 1.0000	D(G(z)): 1.0000 / 1.0000
[56/400][0/29]	Loss_D: 27.6310	Loss_G: 0.0000	D(x): 1.0000	D(G(z)): 1.0000 / 1.0000
[57/400][0/29]	Loss_D: 27.6310	Loss_G: 0.0000	D(x): 1.0000	D(G(z)): 1.0000 / 1.0000
[58/400][0/29]	Loss_D: 27.6310	Loss_G: 0.0000	D(x): 1.0000	D(G(z)): 1.0000 / 1.0000
[59/400][0/29]	Loss_D: 27.6310	Loss_G: 0.0000	D(x): 1.0000	D(G(z)): 1.0000 / 1.0000
[60/400][0/29]	Loss_D: 27.6310	Loss_G: 0.0000	D(x): 1.0000	D(G(z)): 1.0000 / 1.0000
[61/400][0/29]	Loss_D: 27.6310	Loss_G: 0.0000	D(x): 1.0000	D(G(z)): 1.0000 / 1.0000
[62/400][0/29]	Loss_D: 27.6310	Loss_G: 0.0000	D(x): 1.0000	D(G(z)): 1.0000 / 1.0000
[63/400][0/29]	Loss_D: 27.6310	Loss_G: 0.0000	D(x): 1.0000	D(G(z)): 1.0000 / 1.0000
[64/400][0/29]	Loss_D: 27.6310	Loss_G: 0.0000	D(x): 1.0000	D(G(z)): 1.0000 / 1.0000
[65/400][0/29]	Loss_D: 27.6310	Loss_G: 0.0000	D(x): 1.0000	D(G(z)): 1.0000 / 1.0000
[66/400][0/29]	Loss_D: 27.6310	Loss_G: 0.0000	D(x): 1.0000	D(G(z)): 1.0000 / 1.0000
[67/400][0/29]	Loss_D: 27.6310	Loss_G: 0.0000	D(x): 1.0000	D(G(z)): 1.0000 / 1.0000
[68/400][0/29]	Loss_D: 27.6310	Loss_G: 0.0000	D(x): 1.0000	D(G(z)): 1.0000 / 1.0000
[69/400][0/29]	Loss_D: 27.6310	Loss_G: 0.0000	D(x): 1.0000	D(G(z)): 1.0000 / 1.0000
[70/400][0/29]	Loss_D: 27.6310	Loss_G: 0.0000	D(x): 1.0000	D(G(z)): 1.0000 / 1.0000
[71/400][0/29]	Loss_D: 27.6310	Loss_G: 0.0000	D(x): 1.0000	D(G(z)): 1.0000 / 1.0000
[72/400][0/29]	Loss_D: 27.6310	Loss_G: 0.0000	D(x): 1.0000	D(G(z)): 1.0000 / 1.0000
[73/400][0/29]	Loss_D: 27.6310	Loss_G: 0.0000	D(x): 1.0000	D(G(z)): 1.0000 / 1.0000
[74/400][0/29]	Loss_D: 27.6310	Loss_G: 0.0000	D(x): 1.0000	D(G(z)): 1.0000 / 1.0000
[75/400][0/29]	Loss_D: 27.6310	Loss_G: 0.0000	D(x): 1.0000	D(G(z)): 1.0000 / 1.0000
[76/400][0/29]	Loss_D: 27.6310	Loss_G: 0.0000	D(x): 1.0000	D(G(z)): 1.0000 / 1.0000
[77/400][0/29]	Loss_D: 27.6310	Loss_G: 0.0000	D(x): 1.0000	D(G(z)): 1.0000 / 1.0000
[78/400][0/29]	Loss_D: 27.6310	Loss_G: 0.0000	D(x): 1.0000	D(G(z)): 1.0000 / 1.0000
[79/400][0/29]	Loss_D: 27.6310	Loss_G: 0.0000	D(x): 1.0000	D(G(z)): 1.0000 / 1.0000
[80/400][0/29]	Loss_D: 27.6310	Loss_G: 0.0000	D(x): 1.0000	D(G(z)): 1.0000 / 1.0000
[81/400][0/29]	Loss_D: 27.6310	Loss_G: 0.0000	D(x): 1.0000	D(G(z)): 1.0000 / 1.0000
[82/400][0/29]	Loss_D: 27.6310	Loss_G: 0.0000	D(x): 1.0000	D(G(z)): 1.0000 / 1.0000
[83/400][0/29]	Loss_D: 27.6310	Loss_G: 0.0000	D(x): 1.0000	D(G(z)): 1.0000 / 1.0000
[84/400][0/29]	Loss_D: 27.6310	Loss_G: 0.0000	D(x): 1.0000	D(G(z)): 1.0000 / 1.0000
[85/400][0/29]	Loss_D: 27.6310	Loss_G: 0.0000	D(x): 1.0000	D(G(z)): 1.0000 / 1.0000
[86/400][0/29]	Loss_D: 27.6310	Loss_G: 0.0000	D(x): 1.0000	D(G(z)): 1.0000 / 1.0000
[87/400][0/29]	Loss_D: 27.6310	Loss_G: 0.0000	D(x): 1.0000	D(G(z)): 1.0000 / 1.0000
[88/400][0/29]	Loss_D: 27.6310	Loss_G: 0.0000	D(x): 1.0000	D(G(z)): 1.0000 / 1.0000
[89/400][0/29]	Loss_D: 27.6310	Loss_G: 0.0000	D(x): 1.0000	D(G(z)): 1.0000 / 1.0000
[90/400][0/29]	Loss_D: 27.6310	Loss_G: 0.0000	D(x): 1.0000	D(G(z)): 1.0000 / 1.0000
[91/400][0/29]	Loss_D: 27.6310	Loss_G: 0.0000	D(x): 1.0000	D(G(z)): 1.0000 / 1.0000
[92/400][0/29]	Loss_D: 27.6310	Loss_G: 0.0000	D(x): 1.0000	D(G(z)): 1.0000 / 1.0000
[93/400][0/29]	Loss_D: 27.6310	Loss_G: 0.0000	D(x): 1.0000	D(G(z)): 1.0000 / 1.0000
[94/400][0/29]	Loss_D: 27.6310	Loss_G: 0.0000	D(x): 1.0000	D(G(z)): 1.0000 / 1.0000
[95/400][0/29]	Loss_D: 27.6310	Loss_G: 0.0000	D(x): 1.0000	D(G(z)): 1.0000 / 1.0000
[96/400][0/29]	Loss_D: 27.6310	Loss_G: 0.0000	D(x): 1.0000	D(G(z)): 1.0000 / 1.0000
[97/400][0/29]	Loss_D: 27.6310	Loss_G: 0.0000	D(x): 1.0000	D(G(z)): 1.0000 / 1.0000
[98/400][0/29]	Loss_D: 27.6310	Loss_G: 0.0000	D(x): 1.0000	D(G(z)): 1.0000 / 1.0000
[99/400][0/29]	Loss_D: 27.6310	Loss_G: 0.0000	D(x): 1.0000	D(G(z)): 1.0000 / 1.0000
[100/400][0/29]	Loss_D: 27.6310	Loss_G: 0.0000	D(x): 1.0000	D(G(z)): 1.0000 / 1.0000
[101/400][0/29]	Loss_D: 27.6310	Loss_G: 0.0000	D(x): 1.0000	D(G(z)): 1.0000 / 1.0000
[102/400][0/29]	Loss_D: 27.6310	Loss_G: 0.0000	D(x): 1.0000	D(G(z)): 1.0000 / 1.0000
[103/400][0/29]	Loss_D: 27.6310	Loss_G: 0.0000	D(x): 1.0000	D(G(z)): 1.0000 / 1.0000
[104/400][0/29]	Loss_D: 27.6310	Loss_G: 0.0000	D(x): 1.0000	D(G(z)): 1.0000 / 1.0000
[105/400][0/29]	Loss_D: 27.6310	Loss_G: 0.0000	D(x): 1.0000	D(G(z)): 1.0000 / 1.0000
[106/400][0/29]	Loss_D: 27.6310	Loss_G: 0.0000	D(x): 1.0000	D(G(z)): 1.0000 / 1.0000
[107/400][0/29]	Loss_D: 27.6310	Loss_G: 0.0000	D(x): 1.0000	D(G(z)): 1.0000 / 1.0000
[108/400][0/29]	Loss_D: 27.6310	Loss_G: 0.0000	D(x): 1.0000	D(G(z)): 1.0000 / 1.0000
[109/400][0/29]	Loss_D: 27.6310	Loss_G: 0.0000	D(x): 1.0000	D(G(z)): 1.0000 / 1.0000
[110/400][0/29]	Loss_D: 27.6310	Loss_G: 0.0000	D(x): 1.0000	D(G(z)): 1.0000 / 1.0000
[111/400][0/29]	Loss_D: 27.6310	Loss_G: 0.0000	D(x): 1.0000	D(G(z)): 1.0000 / 1.0000
[112/400][0/29]	Loss_D: 27.6310	Loss_G: 0.0000	D(x): 1.0000	D(G(z)): 1.0000 / 1.0000
[113/400][0/29]	Loss_D: 27.6310	Loss_G: 0.0000	D(x): 1.0000	D(G(z)): 1.0000 / 1.0000
[114/400][0/29]	Loss_D: 27.6310	Loss_G: 0.0000	D(x): 1.0000	D(G(z)): 1.0000 / 1.0000
[115/400][0/29]	Loss_D: 27.6310	Loss_G: 0.0000	D(x): 1.0000	D(G(z)): 1.0000 / 1.0000
[116/400][0/29]	Loss_D: 27.6310	Loss_G: 0.0000	D(x): 1.0000	D(G(z)): 1.0000 / 1.0000
[117/400][0/29]	Loss_D: 27.6310	Loss_G: 0.0000	D(x): 1.0000	D(G(z)): 1.0000 / 1.0000
[118/400][0/29]	Loss_D: 27.6310	Loss_G: 0.0000	D(x): 1.0000	D(G(z)): 1.0000 / 1.0000
[119/400][0/29]	Loss_D: 27.6310	Loss_G: 0.0000	D(x): 1.0000	D(G(z)): 1.0000 / 1.0000
[120/400][0/29]	Loss_D: 27.6310	Loss_G: 0.0000	D(x): 1.0000	D(G(z)): 1.0000 / 1.0000
[121/400][0/29]	Loss_D: 27.6310	Loss_G: 0.0000	D(x): 1.0000	D(G(z)): 1.0000 / 1.0000
[122/400][0/29]	Loss_D: 27.6310	Loss_G: 0.0000	D(x): 1.0000	D(G(z)): 1.0000 / 1.0000
[123/400][0/29]	Loss_D: 27.6310	Loss_G: 0.0000	D(x): 1.0000	D(G(z)): 1.0000 / 1.0000
[124/400][0/29]	Loss_D: 27.6310	Loss_G: 0.0000	D(x): 1.0000	D(G(z)): 1.0000 / 1.0000
[125/400][0/29]	Loss_D: 27.6310	Loss_G: 0.0000	D(x): 1.0000	D(G(z)): 1.0000 / 1.0000
[126/400][0/29]	Loss_D: 27.6310	Loss_G: 0.0000	D(x): 1.0000	D(G(z)): 1.0000 / 1.0000
[127/400][0/29]	Loss_D: 27.6310	Loss_G: 0.0000	D(x): 1.0000	D(G(z)): 1.0000 / 1.0000
[128/400][0/29]	Loss_D: 27.6310	Loss_G: 0.0000	D(x): 1.0000	D(G(z)): 1.0000 / 1.0000
[129/400][0/29]	Loss_D: 27.6310	Loss_G: 0.0000	D(x): 1.0000	D(G(z)): 1.0000 / 1.0000
[130/400][0/29]	Loss_D: 27.6310	Loss_G: 0.0000	D(x): 1.0000	D(G(z)): 1.0000 / 1.0000
[131/400][0/29]	Loss_D: 27.6310	Loss_G: 0.0000	D(x): 1.0000	D(G(z)): 1.0000 / 1.0000
[132/400][0/29]	Loss_D: 27.6310	Loss_G: 0.0000	D(x): 1.0000	D(G(z)): 1.0000 / 1.0000
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[134/400][0/29]	Loss_D: 27.6310	Loss_G: 0.0000	D(x): 1.0000	D(G(z)): 1.0000 / 1.0000
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[137/400][0/29]	Loss_D: 27.6310	Loss_G: 0.0000	D(x): 1.0000	D(G(z)): 1.0000 / 1.0000
[138/400][0/29]	Loss_D: 27.6310	Loss_G: 0.0000	D(x): 1.0000	D(G(z)): 1.0000 / 1.0000
[139/400][0/29]	Loss_D: 27.6310	Loss_G: 0.0000	D(x): 1.0000	D(G(z)): 1.0000 / 1.0000
[140/400][0/29]	Loss_D: 27.6310	Loss_G: 0.0000	D(x): 1.0000	D(G(z)): 1.0000 / 1.0000
[141/400][0/29]	Loss_D: 27.6310	Loss_G: 0.0000	D(x): 1.0000	D(G(z)): 1.0000 / 1.0000
[142/400][0/29]	Loss_D: 27.6310	Loss_G: 0.0000	D(x): 1.0000	D(G(z)): 1.0000 / 1.0000
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[145/400][0/29]	Loss_D: 27.6310	Loss_G: 0.0000	D(x): 1.0000	D(G(z)): 1.0000 / 1.0000
[146/400][0/29]	Loss_D: 27.6310	Loss_G: 0.0000	D(x): 1.0000	D(G(z)): 1.0000 / 1.0000
[147/400][0/29]	Loss_D: 27.6310	Loss_G: 0.0000	D(x): 1.0000	D(G(z)): 1.0000 / 1.0000
[148/400][0/29]	Loss_D: 27.6310	Loss_G: 0.0000	D(x): 1.0000	D(G(z)): 1.0000 / 1.0000
[149/400][0/29]	Loss_D: 27.6310	Loss_G: 0.0000	D(x): 1.0000	D(G(z)): 1.0000 / 1.0000
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[151/400][0/29]	Loss_D: 27.6310	Loss_G: 0.0000	D(x): 1.0000	D(G(z)): 1.0000 / 1.0000
[152/400][0/29]	Loss_D: 27.6310	Loss_G: 0.0000	D(x): 1.0000	D(G(z)): 1.0000 / 1.0000
[153/400][0/29]	Loss_D: 27.6310	Loss_G: 0.0000	D(x): 1.0000	D(G(z)): 1.0000 / 1.0000
[154/400][0/29]	Loss_D: 27.6310	Loss_G: 0.0000	D(x): 1.0000	D(G(z)): 1.0000 / 1.0000
[155/400][0/29]	Loss_D: 27.6310	Loss_G: 0.0000	D(x): 1.0000	D(G(z)): 1.0000 / 1.0000
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[157/400][0/29]	Loss_D: 27.6310	Loss_G: 0.0000	D(x): 1.0000	D(G(z)): 1.0000 / 1.0000
[158/400][0/29]	Loss_D: 27.6310	Loss_G: 0.0000	D(x): 1.0000	D(G(z)): 1.0000 / 1.0000
[159/400][0/29]	Loss_D: 27.6310	Loss_G: 0.0000	D(x): 1.0000	D(G(z)): 1.0000 / 1.0000
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[161/400][0/29]	Loss_D: 27.6310	Loss_G: 0.0000	D(x): 1.0000	D(G(z)): 1.0000 / 1.0000
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[163/400][0/29]	Loss_D: 27.6310	Loss_G: 0.0000	D(x): 1.0000	D(G(z)): 1.0000 / 1.0000
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[166/400][0/29]	Loss_D: 27.6310	Loss_G: 0.0000	D(x): 1.0000	D(G(z)): 1.0000 / 1.0000
[167/400][0/29]	Loss_D: 27.6310	Loss_G: 0.0000	D(x): 1.0000	D(G(z)): 1.0000 / 1.0000
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[171/400][0/29]	Loss_D: 27.6310	Loss_G: 0.0000	D(x): 1.0000	D(G(z)): 1.0000 / 1.0000
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[192/400][0/29]	Loss_D: 27.6310	Loss_G: 0.0000	D(x): 1.0000	D(G(z)): 1.0000 / 1.0000
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---------------------------------------
KeyboardInterruptTraceback (most recent call last)
<timed exec> in <module>

~/gan_plankton/src/models/models.py in train(self, dataloader, num_epochs)
    144         for epoch in range(num_epochs):
    145             # For each batch in the dataloader
--> 146             for i, data in enumerate(dataloader, 0):
    147 
    148                 ############################

~/anaconda3/envs/ganenv/lib/python3.8/site-packages/torch/utils/data/dataloader.py in __next__(self)
    343 
    344     def __next__(self):
--> 345         data = self._next_data()
    346         self._num_yielded += 1
    347         if self._dataset_kind == _DatasetKind.Iterable and \

~/anaconda3/envs/ganenv/lib/python3.8/site-packages/torch/utils/data/dataloader.py in _next_data(self)
    839 
    840             assert not self._shutdown and self._tasks_outstanding > 0
--> 841             idx, data = self._get_data()
    842             self._tasks_outstanding -= 1
    843 

~/anaconda3/envs/ganenv/lib/python3.8/site-packages/torch/utils/data/dataloader.py in _get_data(self)
    806         else:
    807             while True:
--> 808                 success, data = self._try_get_data()
    809                 if success:
    810                     return data

~/anaconda3/envs/ganenv/lib/python3.8/site-packages/torch/utils/data/dataloader.py in _try_get_data(self, timeout)
    759         #   (bool: whether successfully get data, any: data if successful else None)
    760         try:
--> 761             data = self._data_queue.get(timeout=timeout)
    762             return (True, data)
    763         except Exception as e:

~/anaconda3/envs/ganenv/lib/python3.8/multiprocessing/queues.py in get(self, block, timeout)
    105                 if block:
    106                     timeout = deadline - time.monotonic()
--> 107                     if not self._poll(timeout):
    108                         raise Empty
    109                 elif not self._poll():

~/anaconda3/envs/ganenv/lib/python3.8/multiprocessing/connection.py in poll(self, timeout)
    255         self._check_closed()
    256         self._check_readable()
--> 257         return self._poll(timeout)
    258 
    259     def __enter__(self):

~/anaconda3/envs/ganenv/lib/python3.8/multiprocessing/connection.py in _poll(self, timeout)
    422 
    423     def _poll(self, timeout):
--> 424         r = wait([self], timeout)
    425         return bool(r)
    426 

~/anaconda3/envs/ganenv/lib/python3.8/multiprocessing/connection.py in wait(object_list, timeout)
    928 
    929             while True:
--> 930                 ready = selector.select(timeout)
    931                 if ready:
    932                     return [key.fileobj for (key, events) in ready]

~/anaconda3/envs/ganenv/lib/python3.8/selectors.py in select(self, timeout)
    413         ready = []
    414         try:
--> 415             fd_event_list = self._selector.poll(timeout)
    416         except InterruptedError:
    417             return ready

KeyboardInterrupt: 

Visualize training stats

In [ ]:
plot_loss(gan.G_losses, gan.D_losses)
In [ ]:
generator_progress(gan.img_list)
In [ ]:
compare_fake_real(data_loader, gan.device, gan.img_list)

Use models

In [ ]:
fake_batch = gan.generate(torch.randn(64, gan.generator.latent_size, 1, 1, device=gan.device))
print_batch_images([fake_batch], gan.device)
In [ ]:
gan.predict_discriminator(next(iter(data_loader))[0])